Job Summary:

• Confirms that the team members understand the addressed scientific questions and the data interpretation
• Applies and develops analytical methods and predictive models that deliver impact on research and drug development programs
• Contributes to the identification and preparation of chem/biomedical datasets for application
• Develops key results and quality benchmarks for data, models and impact, in collaboration with scientific users
• Creates approaches, methods and models iteratively and communicates results effectively to non-data scientist associates, by supporting expert introspection at each stage
• Applies expertise in machine learning, deep learning, data visualization and structured/unstructured data analytics, towards the scientific goals of the team\
• Evaluate the performance of new features and content
• Effectively write, present, and communicate research results and recommendations
• Continually improve data science practice

Skills on Resume: 

• Scientific Communication (Soft Skills)
• Analytical Methods (Hard Skills)
• Dataset Preparation (Hard Skills)
• Quality Benchmarking (Hard Skills)
• Results Communication (Soft Skills)
• Machine Learning (Hard Skills)
• Performance Evaluation (Hard Skills)
• Continuous Improvement (Soft Skills)

Job Summary:

• Develop the AI algorithms, data management, and data pipeline
• Develop and execute a data platform strategy for the Urban Air Mobility system
• Work closely with key stakeholders including the engineering team, program management, strategy, finance, business operations, and external partners
• Provide guidance to the executive leadership team on critical technology decisions
• Define and maintain progress metrics to keep the team and management up-to-date on status, KPIs, risk, and mitigation plans
• Work with Systems Architecture, Design, and Engineering teams to define the technology roadmap and scope development effort
• Identify, evaluate, qualify, select, and manage third-party development firms to augment and scale the core team
• Lead team to efficiently deliver high-quality code and features on time and on budget
• Foster cross-functional collaboration and productivity and effectively manage conflicts

Skills on Resume: 

• AI Algorithms (Hard Skills)
• Data Management (Hard Skills)
• Stakeholder Collaboration (Soft Skills)
• Executive Guidance (Soft Skills)
• Progress Metrics (Hard Skills)
• Technology Roadmap (Hard Skills)
• Vendor Management (Soft Skills)
• Team Leadership (Soft Skills)

Job Summary:

• Collaborate with internal stakeholders/customers to identify business problems and provide meaningful, actionable insights
• Processing, cleansing, manipulating, and verifying the integrity of data used for analyses
• Create training data sets and perform cross-validation to test the efficiency of the resulting algorithms
• Apply statistical techniques and machine learning approaches to a wide variety of business problems
• Multivariate statistical analysis of health business trends to inform decision-making regarding future sustainable affordability of the business
• Provide analytical support services to optimize contract negotiations and provider (hospital, medical and ancillary) reviews
• Get the opportunity to work with a high-performing team and be exposed to opportunities to advance skills and career.
• Work closely with Data Platform engineers for the entire life-cycle of data science, including pre-processing, modeling & training, and eventual GO-LIVE.
• Working closely with the Product Manager, User Acquisition Analyst, and Content Manager to discover patterns of core content of books, usage, and performance in user acquisition through various media channels.
• Drive prediction analysis for revenue, ROI, and various metrics of the content delivery pipeline, from content acquisition, production, user acquisition, to monetization
• Run some A/B tests to optimize the in-app user experience

Skills on Resume: 

• Business Insights (Soft Skills)
• Data Cleansing (Hard Skills)
• Training Sets (Hard Skills)
• Statistical Techniques (Hard Skills)
• Analytical Support (Soft Skills)
• Team Collaboration (Soft Skills)
• Prediction Analysis (Hard Skills)
• AB Testing (Hard Skills)

Job Summary:

• Report to the Chief Economist and Head of Strategy, Research, and Analytics
• Interface with many departments, providing research and problem-solving functions focused on improving processes and business opportunities.
• Work closely with the Data, Business Development, Risk, FP&A, and IT departments to create and produce content in conjunction with business line needs.
• Moderately visible to senior management, and the departmental work products are often presented in company committee meetings as well as to the board of directors.
• Develop, maintain, and validate analytical tools, models, and datasets used for monitoring and assessing the market
• Maintain and enhance deployed quantitative and predictive models (e.g., credit-loss prediction models, binary prepayment models, etc.)
• Develop custom data models and algorithms using a wide range of enterprise and industry data (e.g., lending workflow algorithms, geospatial regression analysis, customer and loan behavior anomaly detection, etc.)
• Interpret data, analyze results using statistical techniques, and provide ongoing reporting
• Identify, analyze, and interpret trends or patterns in complex data sets
• Participate in and help guide the enterprise data governance framework.

Skills on Resume: 

• Research Reporting (Soft Skills)
• Cross-Functional Collaboration (Soft Skills)
• Analytical Tools (Hard Skills)
• Predictive Modeling (Hard Skills)
• Custom Algorithms (Hard Skills)
• Statistical Analysis (Hard Skills)
• Trend Identification (Hard Skills)
• Data Governance (Hard Skills)

Job Summary:

• Performing, sampling and weighting according to the defined methodology for surveys.
• Making recommendations to improve questionnaire design.
• Controlling the quality of the survey database and enhancing the routine of the data checks.
• Related to Panel Sample selection, RIM Weighting design and Universes updates
• Performing complex analyses to specify the panel sample design.
• Performing and analyzing the tests on new universes/weighting structures implemented in the production system.
• Evaluating the effect of the new RW structure on the viewing.
• Executes tests on new universes/weighting structures in the test environment
• Check the accuracy of the implementation.

Skills on Resume: 

• Sampling Methodology (Hard Skills)
• Questionnaire Design (Hard Skills)
• Data Quality (Hard Skills)
• Panel Selection (Hard Skills)
• Complex Analysis (Hard Skills)
• Test Execution (Hard Skills)
• Effect Evaluation (Hard Skills)
• Accuracy Checking (Hard Skills)

Job Summary:

• Working as a team to find patterns in large data sets, including the building of bespoke models that answer specific questions posed by stakeholders
• Lead the development of production-ready Python code that enables to deploy algorithms for use by colleagues and other Morrisons systems
• Mentor junior members of the team, both in terms of technical development and softer business skills
• Work closely with data analysts in reporting teams, to ensure it have access to the right "models" to answer questions and receive support and guidance on when models should be used
• Engaging with cross-functional teams to understand key business requirements
• Meeting with a variety of stakeholders to discuss data project requirements and taking action from these conversations
• Creating actionable recommendations from findings and communicating them in a compelling way that is customer-friendly and easy to follow.
• Work directly with the government client to gather requirements, strategize, and plan data analytics initiatives and projects.
• Use subject matter expertise to conduct analytics and analysis for complex use cases.
• Utilize statistical models, algorithms, machine learning, trend analysis, and predictive analysis.
• Identify patterns and relationships within large amounts of disparate data sets.

Skills on Resume: 

• Pattern Recognition (Hard Skills)
• Python Development (Hard Skills)
• Mentoring Skills (Soft Skills)
• Cross-Functional Collaboration (Soft Skills)
• Stakeholder Engagement (Soft Skills)
• Actionable Recommendations (Soft Skills)
• Subject Expertise (Hard Skills)
• Predictive Analysis (Hard Skills)

Job Summary:

• Analyze/interpret data compilations and provide new insights
• Create and find new ways of advancing business performance regarding television scheduling, etc
• Develop solutions to various company challenges
• Build models and utilize statistics, probability theories, etc
• Provide working knowledge and understanding of business reality
• Work alongside various departments including finance, marketing, and programs
• Identify valuable data sources and discover trends
• Ensure the quality and accuracy of data collection
• Clearly communicate findings to diverse audiences using visual, interactive, and dynamic work products.
• Assist with the development of data analytics pipelines, platforms, and applications

Skills on Resume: 

• Data Interpretation (Hard Skills)
• Business Advancement (Soft Skills)
• Solution Development (Soft Skills)
• Statistical Modeling (Hard Skills)
• Business Acumen (Soft Skills)
• Cross-Department Collaboration (Soft Skills)
• Trend Identification (Hard Skills)
• Data Quality (Hard Skills)

Job Summary:

• Partner with businesses to identify opportunities and develop data-driven solutions to improve business outcomes.
• Partner with the internal data services team to ensure proper data is captured in analytical environments, establish data pipelines, implement models, and monitor outcomes.
• Partner with the Innovation and Digital Transformation team to build new digital products and analytic models for assessing the effectiveness of digital solutions to improve user experience.
• Work in Microsoft Azure and SQL Server environments to develop models.
• Develop and experiment with new algorithms and models to maximize long-term member value.
• Leverage data and insights to inform decision-making on some of the most critical topics around acquisition, retention, personalization, and product development.
• Creatively synthesize internal data (bank account information, demographic information) with outside data sources to develop meaningful insights.
• Present findings and solutions to various levels of management.
• Stay updated with industry and data science technology trends.

Skills on Resume: 

• Business Partnership (Soft Skills)
• Data Pipeline (Hard Skills)
• Digital Innovation (Soft Skills)
• Azure SQL (Hard Skills)
• Algorithm Development (Hard Skills)
• Data-Driven Decision (Soft Skills)
• Insight Synthesis (Hard Skills)
• Presentation Skills (Soft Skills)

Job Summary:

• Provide computational expertise, cleaning data and data structures
• Defining and developing methods and analyzing
• Extracting biological and process insights
• Suggesting further experiments and improvements in experimental design
• Convey results in a meaningful way to computational and experimental scientists with various backgrounds
• Own user data requests to aid in data-driven decision-making needs across strain engineering, analytics and fermentation teams
• Work with the computing team to evaluate, deploy, and refine solutions like data warehouses, ETL analyses, analysis tools, and visualization infrastructure to support users and to ensure principled data capture
• Provide training in computing and analysis skills in a variety of tools (e.g., SQL, R, Jupyter notebooks, Spotfire, JMP)
• Work with the CIO to ensure long-term, scalable and efficient solutions
• Build and maintain dashboards for core operational metrics (e.g. network reliability, growth funnel)

Skills on Resume: 

• Computational Expertise (Hard Skills)
• Experimental Design (Hard Skills)
• Results Communication (Soft Skills)
• User Support (Soft Skills)
• Data Warehousing (Hard Skills)
• Technical Training (Soft Skills)
• Scalable Solutions (Hard Skills)
• Dashboard Development (Hard Skills)

Job Summary:

• Working closely with key stakeholders to understand business questions and execute data science projects that deliver business solutions
• Working on complex and extremely varied data sets from some of Australia’s largest organisations to solve business problems that make a tangible difference
• Developing data science products and solutions for stakeholders as well as for the data science team
• End-to-end data science execution including scoping, building, testing, implementation, maintenance, tracking and optimisation of predictive models
• Writing highly optimized code to advance the internal Data Science Toolbox
• Working in a multi-disciplinary environment with specialists in machine learning, engineering, and data engineering
• Adding real-world impact to academic expertise
• Write papers and present at meetings to non-technical stakeholders
• Work closely with the other members of the team to ensure models are easy to deploy.
• Advocate for data science within Admiral, helping the business understand where and when it can add value to processes.
• Contribute to the training and development of graduate data scientists
• Contribute to the data scientist community within Admiral in a positive way

Skills on Resume: 

• Stakeholder Collaboration (Soft Skills)
• Complex Data (Hard Skills)
• Product Development (Hard Skills)
• Model Execution (Hard Skills)
• Optimized Coding (Hard Skills)
• Cross-Disciplinary (Soft Skills)
• Academic Impact (Soft Skills)
• Team Advocacy (Soft Skills)

Job Summary:

• Manage multiple global consumer analytics projects simultaneously to provide insights, dashboards/reporting and recommended business actions.
• Develop and apply data science techniques including segmentation, affinity/propensity models, consumer or product category deep dives, marketing effectiveness, consumer lifetime value and consumer journey analytics.
• Collaborate with VF Corporate teams to coordinate and align on key consumer data and analytics projects.
• Propose and implement continuous efforts to improve data acquisition and analytics methodologies to further enhance CLM team capabilities.
• Mentor junior team members on how to use more advanced methods to solve business problems more efficiently.
• Diverse experiences and backgrounds enable you to provide a unique perspective to fuel global growth.
• Present key insights and business recommendations to large groups and/or senior leadership teams.
• Provide important and relevant analyses of transactional and consumer data to drive marketing and business decisions that result in increased revenue, consumer experience and brand affinity.
• Collaborate with various internal clients to add value to field of expertise by understanding consumers’ behavior, recommending action plans and analyzing critical results.
• Solve business problems using a range of advanced statistical, machine learning and artificial intelligence techniques.
• Research new ideas and stay up to date with the world of data science

Skills on Resume: 

• Project Management (Soft Skills)
• Data Science (Hard Skills)
• Cross-Functional Collaboration (Soft Skills)
• Methodology Improvement (Hard Skills)
• Mentoring Skills (Soft Skills)
• Business Perspective (Soft Skills)
• Insight Presentation (Soft Skills)
• Advanced Analytics (Hard Skills)

Job Summary:

• Working closely with the Engineering team to unlock growth capital for founders
• Using Statistics and Machine Learning to provide solutions and insights across the organization
• Improving data-driven underwriting and risk strategy
• Conducting exploratory data analyses
• Applying real-world data mining approaches
• Implementing end-to-end machine learning models
• Improving the experiment tracking framework
• Own the methodologies behind how we measure ourselves and create new metrics as the business evolves
• Clean and organize data warehouse, manage scheduled aggregations, and expose rich views of data to stakeholders
• Investigations into trickiest problems, finding approachable ways to present and visualize findings to the rest of the company
• Chart out Common’s data roadmap, striking the right balance between quick-and-dirty analysis vs. building out robust, scalable data flows.

Skills on Resume: 

• Growth Capital (Soft Skills)
• Machine Learning (Hard Skills)
• Risk Strategy (Hard Skills)
• Exploratory Analysis (Hard Skills)
• Data Mining (Hard Skills)
• Experiment Tracking (Hard Skills)
• Data Management (Hard Skills)
• Data Visualization (Soft Skills)

Job Summary:

• Design and implement analytical data products used to enhance customer and business user interactions and business decisions throughout the corporation
• Reports to the Director of Business Reporting & Analytics, and as part of the Enterprise Performance Management & Analytics team
• Support all levels of management at corporate, groups and divisions, across multiple functional areas and countries.
• Create, maintain, and report on a monthly, quarterly, and annual basis, key metrics for defined areas of expertise.
• Builds and maintains online and off-line predictive models for various key performance measures and or forecasts at the enterprise, group and division levels
• Groupings like sales forces and or clusters of customer populations, and communicates results to decision-makers for follow-up action.
• Identify and investigate trends that warrant deeper analysis, and advise decision-makers of implications and potential corrective actions.
• Develop and manage data quality and normalization and attribution models and metrics needed to make multiple disparate data sources used for data mining and other analytical uses
• Monitor and adapt models to changing business needs
• Define and provide input for experiment design and quantitative analysis within the area of expertise.
• Support Ad hoc requests as a leader, advisor or contributing team member for key projects
• Manage the integration of key external data sources into enterprise data repositories for use by all analytics teams and report writers across the enterprise
• Design and manage pattern databases for use in predictive modeling and other data mining analysis
• Confirm with and contribute to Enterprise Performance Management & Analytics governance processes and policies

Skills on Resume: 

• Analytical Design (Hard Skills)
• Performance Reporting (Hard Skills)
• Management Support (Soft Skills)
• Predictive Modeling (Hard Skills)
• Trend Analysis (Hard Skills)
• Data Quality (Hard Skills)
• Experiment Design (Hard Skills)
• Data Integration (Hard Skills)

Job Summary:

• Develop & help implement strategic analytical and data mining solutions to understand key business behaviors such as customer acquisition, product up-sell, customer retention, lifetime value, channel preferences, customer satisfaction and loyalty drivers, etc.
• Help to create and deliver project proposals and guide strategic thinking on offering analytics consulting services to clients
• Consult with clients to gain an understanding of the current state of the business area(s), immediate and long-term needs, any KPI goals, and to determine what success looks like
• Consult heavily with business users and stakeholders
• Identify, capture and leverage appropriate data sources across areas of the business,
• Ensure that analytical solutions are tailored to business needs
• Support or result in actionable customer strategies,
• Determine delivery & implementation options
• Lead analytics and strategy engagements
• Provide project-specific guidance to team members in performing analyses and delivering strategic recommendations
• Create and maintain project plans, project schedules, and other project documentation
• Provide statistical methodology and project management support for commercial deliverables as well as custom studies
• Measure results and profitability of business solutions, including determining the marginal impact of actions on behaviors
• Create test designs (DOE), determine sample sizes, etc., for marketing campaigns
• Conduct statistical analyses and derive conclusions from output/results, and identify new opportunities for standard reports and value-added analytics
• Develop new applications and methodologies for existing or newly acquired data
• Provides detailed written summaries of results, analyses of marketing and promotional effectiveness, measuring the value of analytical solutions and reinforcing the value proposition of data mining
• Create detailed project documentation and maintain a library of past work to enable continuous learning

Skills on Resume: 

• Strategic Analytics (Hard Skills)
• Client Consulting (Soft Skills)
• Stakeholder Engagement (Soft Skills)
• Data Sourcing (Hard Skills)
• Project Management (Soft Skills)
• Statistical Methodology (Hard Skills)
• Test Design (Hard Skills)
• Result Measurement (Hard Skills)

Job Summary:

• Manages and transforms very large data sets
• Works on moderate to complex projects that require a singular area of expertise
• Leads project planning sessions with users, business analysts, and team members to gather and analyze user requirements.
• Formulates mathematical models in an appropriate programming language or application
• Analyzes raw input data from a computer or other media
• Validates and tests of models to ensure adequacy, or determines the need for reformulation
• Utilizes and stays current on applicable programming languages and software technologies
• Tracks progress and reports out to stakeholders
• Knows what quality means, strives for quality, designs for quality, tests and refines until a very high quality is achieved, and continuously improves
• Delivers prototypes/proofs of concept and develops recommendations
• Recommends plans to bring to Production
• Manages and maintains non-trivial software artifacts that achieve the capabilities listed above
• Strives to create clean, widely applicable/reusable artifacts
• Participates in daily scrum team meetings and other agile ceremonies
• Operates with minimal supervision required (supervision by manager and product owner a couple of times per week)

Skills on Resume: 

• Data Management (Hard Skills)
• Project Leadership (Soft Skills)
• Mathematical Modeling (Hard Skills)
• Data Analysis (Hard Skills)
• Model Validation (Hard Skills)
• Programming Expertise (Hard Skills)
• Progress Reporting (Soft Skills)
• Quality Focus (Soft Skills)

Job Summary:

• Lead the team in developing sophisticated predictive models, mining large data sets for insights, building scalable data products, and growing the overall Data Science capability. 
• Serve as the senior member on project teams, often creating solutions from scratch, or applying known and proven techniques effectively. 
• Versed in multiple analytical techniques, and can seamlessly transition between projects, data types, and problems.
• Closely follows the direction set by delivery management and senior team members to achieve common goals. 
• Assist senior team members in collecting client requirements
• Analyze requirements, configuration, testing and validation of the software application.
• Works closely with the Data Engineering and Product teams to ensure the successful completion of projects.
• Decomposes problem statements into specific deliverables and requirements.
• Supports the Product Owners in developing sprint goals and roadmaps.
• Continuously scans the Data Science landscape for recent developments and opportunities to integrate new methodologies into the existing project portfolio.
• Creates presentations and delivers results to colleagues, stakeholders and executive leadership.
• Leads peer review sessions and collaborative exercises to build the team’s overall analytical capability.
• Performs data aggregations, joins, manipulations, and cleaning to ensure data integrity throughout the entire analytical process.
• Applies supervised and unsupervised modeling techniques to data to generate predictions and uncover patterns.
• Develops hypothesis statements and applies statistical testing to determine causality and generalize observations.
• Solves problems by applying a variety of predictive modeling/machine learning/deep learning techniques.
• Maintains a comprehensive understanding of the current analytical landscape, including emergent technologies and methods.

Skills on Resume: 

• Predictive Modeling (Hard Skills)
• Project Leadership (Soft Skills)
• Analytical Techniques (Hard Skills)
• Client Requirements (Soft Skills)
• Data Engineering (Hard Skills)
• Problem Decomposition (Soft Skills)
• Presentation Skills (Soft Skills)
• Statistical Testing (Hard Skills)

Job Summary:

• Support the EMEA Data Scientist in managing, coordinating and advising strategic and high-impact global analytics projects
• Contribute to defining and developing the business intelligence model for EMEA region
• Support the digitalization strategy and contribute to EMEA Sales and Marketing productivity improvement
• Assist with the training of the analytics community, and shape the analytics framework for the organization
• Advise peers and other teams on how to improve data maturity and identify compelling data opportunities
• Up to date with the most recent data technologies and actively share knowledge within the organization (e.g., support data analytics workshops)
• Contribute to the global knowledge pool
• Assisting with the conduct of end-to-end analyses from the idea phase all the way through to end results including the presentation and communication of findings
• Perform exploratory data analyses on large and complex data sets using descriptive statistics
• Assist with the application of appropriate statistical or machine learning techniques (regression, classification, clustering) to model complex problems, find opportunities to increase sales productivity, discover solutions, and deliver actionable business insights
• Assist with the design of A/B test experiments, analyze and interpret the results of such tests
• Create reports and dashboards that capture key metrics required by senior management
• Assist with the communication of data-driven insights and actionable recommendations to global senior management, translate technical findings for non-technical teams and vice versa
• Automate reports and data workflows (using tools such as Power Automate, etc.)
• Assist with the design, implementation and optimization of ETL workflows
• Manage, maintain, and clean complex datasets in big data environment
• Act as a junior business analyst, gather and document reporting requirements, and turn them into technical requirement specifications
• Actively drive global harmonization and simplification of processes.

Skills on Resume: 

• Project Coordination (Soft Skills)
• Business Intelligence (Hard Skills)
• Digital Strategy (Hard Skills)
• Training Facilitation (Soft Skills)
• Data Maturity (Soft Skills)
• Exploratory Analysis (Hard Skills)
• AB Testing (Hard Skills)
• Report Automation (Hard Skills)

Job Summary:

• Raise a change request to improve diagnostic information collected by the vehicles
• Participate in the critical task force dedicated to troubleshooting
• Report regularly and accurately on the performance of the fleet, for internal use, and to report to the customer.
• Highlight any anomalies in system performance or component failures as present in the data
• Provide the System, Maintenance, development and Reliability engineers with specific analyses.
• Assist in providing training on the company’s data reporting tools.
• Look after the quality of the raw data and report on any inaccuracies or concerns and provide instructions/training on how data is to be recorded and kept
• Assist with the data warehouse activities related to the Fleet Support Center
• Contributes to standardization by reusing existing solutions or by implementing reusable solutions
• Contributes to continuous improvement (Return of Experience, processes)

Skills on Resume: 

• Change Management (Soft Skills)
• Troubleshooting Skills (Soft Skills)
• Performance Reporting (Hard Skills)
• Anomaly Detection (Hard Skills)
• Data Training (Soft Skills)
• Data Quality (Hard Skills)
• Data Warehousing (Hard Skills)
• Continuous Improvement (Soft Skills)

Job Summary:

• Analyzing and selecting the best statistical methodology for solving business questions
• Managing and optimizing data flows and data analyses
• Describe and visualize discovered insights and predictions
• Detecting irregularities in data
• Recognizing patterns in big data and building prediction models
• Identifying questions from business operations
• Deploying predictive algorithms for decision making
• Research and develop possibilities to get even more out of existing data
• Setting up, managing and training a Data Science team
• Reporting and sharing the insights and knowledge gained with management and other stakeholders
• Make coherence in the different types of data

Skills on Resume: 

• Statistical Methodology (Hard Skills)
• Data Optimization (Hard Skills)
• Insight Visualization (Hard Skills)
• Irregularity Detection (Hard Skills)
• Pattern Recognition (Hard Skills)
• Question Identification (Soft Skills)
• Algorithm Deployment (Hard Skills)
• Team Management (Soft Skills)

Job Summary:

• Collaborate with stakeholders to understand product/feature plans for development and translate those plans into experimentation objectives and testable hypotheses
• Assist product teams with experimental design and analyses, including the development of analysis plans and ad hoc reports
• Develop experimentation strategy and project plans for stakeholders and lead execution of plans involving members across multiple teams
• Synthesize data from experimentation and other data sources to provide stakeholders with answers to research questions and help determine next steps for a product/feature using a data-driven approach
• Create and present materials communicating quantitative findings and relevant business impacts to internal and external teams as well as an executive audience
• Refine experimentation processes including the leverage of existing data science tools and the development of new tools
• Leverage multiple data sources to produce intelligent data products that solve the needs of business and engineering for business intelligence, operational analytics, descriptive models, predictive models, diagnostic models, and prescriptive models.
• Coordinate technical activities across projects and the organization
• Interact with various stakeholders to understand business needs, communicate project status and develop relationships to ensure satisfaction
• Develop and deliver materials on experimentation techniques and tools to a broad set of business-intelligence, data, and analytics professionals with varied backgrounds
• Deliver results using metrics-driven analysis, and communicate the costs and tradeoffs of ideas to stakeholders and top management

Skills on Resume: 

• Stakeholder Collaboration (Soft Skills)
• Experimental Design (Hard Skills)
• Project Planning (Soft Skills)
• Data Synthesis (Hard Skills)
• Findings Presentation (Soft Skills)
• Process Refinement (Hard Skills)
• Data Productization (Hard Skills)
• Cross-Functional Coordination (Soft Skills)

Job Summary:

• Represent Marketing Sciences in cross-functional team initiatives and new product launches such as (5G BI, 4G BI, One Fiber, and Fiber Network Expansion).
• Develop product-specific sales plays to guide business strategy for growth. 
• Automate the campaign generation and lead delivery process for Fixed Wireless Access products.
• Lead the ingestion, integration and processing of data from various data providers, sales and IT to consolidate data into one system.
• Represent the unified data using a Tableau dashboard.
• Creating and generating Machine Learning Models using the application of principles, theories, concepts and technologies to optimize campaigns.
• Form initiatives to create data pipelines for real-time feeds to enhance models and explore new sources of data such as location data, web search data and historical sales data to enhance the models.
• Communicate to leadership on active data science findings, efforts, actions and results. 
• Translate business requirements and work with IT to build datasets required for analysis.
• Drive the adoption of analytics in decision making for the Sales Team. 
• Develop data products that can be used by end users to make quick, informative decisions.

Skills on Resume: 

• Cross-Functional Collaboration (Soft Skills)
• Sales Strategy (Hard Skills)
• Process Automation (Hard Skills)
• Data Integration (Hard Skills)
• Dashboard Creation (Hard Skills)
• Machine Learning (Hard Skills)
• Data Pipeline (Hard Skills)
• Leadership Communication (Soft Skills)

Job Summary:

• Build algorithms and work with machine learning and deep learning tools to deliver advanced analytics solutions across the firm including recommendation engines, customized data models, customer journeys, graph models, etc.
• Mine and analyze data from the company’s databases to drive optimization and improvement of business strategies.
• Use predictive modelling to increase and optimize customer journey experiences, revenue generation and other business outcomes.
• Analyze data for trends and patterns and interpret the data with clear objective in mind.
• Execute and review data science projects in an agile manner and in compliance with internal regulatory requirements.
• Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
• Interact with 1-2 squads to identify questions and issues for data analysis.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Skills on Resume: 

• Algorithm Development (Hard Skills)
• Data Mining (Hard Skills)
• Predictive Modeling (Hard Skills)
• Data Interpretation (Hard Skills)
• Project Execution (Soft Skills)
• Insight Identification (Soft Skills)
• Model Monitoring (Hard Skills)
• Effectiveness Assessment (Soft Skills)