Job Summary:

• Work closely with customers to deliver labeled data and relevant insights to customers
• Build well-tested, high-quality, up-to-date, and documented datasets that customer can use to answer their own questions
• Perform exploratory data analysis and insightful dataset summarization highlighting the most interesting aspects of the dataset
• Develop and implement data pipelines that handle parsing, cleansing and enrichment of data to meet customer’s analytics needs
• Communicate findings clearly to a broad range of stakeholders
• Actively contribute to best practices around analytics engineering
• Research and acquire required domain knowledge on industrial assets and processes to enrich the datasets
• Defining and documenting the approach and requirements for data intelligence in processing. 
• Cooperation with PCs and technology experts in engineering, processing, automation and analytics teams.
• Using connected analytics on current assets, building up data intelligence in processing and leading data driven improvement projects to produce cosmetic products with less operational, equipment design and product related losses

Skills on Resume:

• Customer Interaction (Soft Skills)
• Data Engineering (Hard Skills)
• Exploratory Data Analysis (EDA) (Hard Skills)
• Communication (Soft Skills)
• Best Practices (Hard Skills)
• Domain Knowledge (Hard Skills)
• Project Management (Soft Skills)
• Collaboration (Soft Skills)

Job Summary:

• To increase the speed and efficiency of common data team workflows. 
• Improve the overall Data team’s workflow through knowledge sharing, proper documentation, and code review
• Deliver/review new automation frameworks within the team
• Work on efficient ingestion of new data into data warehouse using tools such as Python, Spark, Airflow, ADF, Databricks, Azure Data Lake etc.
• Work on efficient storage of data in the data warehouse, identifying performance improvements from query to table redesign.
• Work on the careful design of the schema, table names, data models and practices within the data warehouse, creating a well-curated data set.
• Rewrite data models using dbt or similar, and empower other analysts to use the frameworks, developing their skills with mentoring and good code review.
• Identify re-usable elements of downstream analytics and move into the repeatable data model
• Contribute to internal Python and R libraries, driving best practice
• Production of reports explaining the conclusions and process of the data treatment.
• Support the Control Center in technical issues with the execution of periodic reports or other programs developed by Data Analytics.
• 
  

Skills on Resume:

• Data Workflow Optimization (Soft Skills)
• Automation and Framework Development (Hard Skills)
• Data Ingestion and Processing (Hard Skills)
• Data Modeling and Design (Hard Skills)
• Analytics and Reporting (Hard Skills)
• Library Contribution and Best Practices (Hard Skills)
• Technical Support (Soft Skills)
• Continuous Improvement (Soft Skills)

Job Summary:

• Creates and improves predictive models to identify patients who could benefit from programs.
• Develops statistical studies to support business questions.
• Develops operational reports and tools that track company performance and deliver insights that improve products and operations.
• Be a knowledge expert on AbleTo’s data sources and model. 
• Work with the business to identify needs for new data sources / types, builds the solution, and then helps the business and Business Insights Team leverage the data effectively
• Actively seek opportunities to operationalize data to automate and improve decision making processes throughout the business
• Ensure relevant data is captured in source systems, and made available for teams within business intelligence applications
• Improve code coverage within modeling layer to enhance data quality and data governance rules
• Automate time-consuming reporting and data discovery processes for end-users
• Create powerful and functional tools to be used by analysts and end-users

Skills on Resume:

• Predictive Modeling (Hard Skills)
• Statistical Analysis (Hard Skills)
• Report Development (Hard Skills)
• Data Knowledge (Hard Skills)
• Data Integration (Hard Skills)
• Operationalizing Data (Hard Skills)
• Data Governance (Hard Skills)
• Code Coverage and Automation (Hard Skills)

Job Summary:

• Provide clean data sets to the BI team.
• Applying best practices like version control and continuous integration to the Analytics code base.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from the data warehouse.
• Assemble large, complex data sets that meet business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and if required, re-designing infrastructure for greater scalability.
• Create reports on Tableau for business end-users.
• Become a member of cross-functional product and data team and provide the team with analytics data
• Take an active part in plannings, sprints, reviews and retros of the product teams
• Understand business goals and convert them into data collection requirements
• Create implementation concepts and technical analytics specifications
• Implement the tracking through the tag manager required for accurate data collection
• Be in close alignment with the future data peers to jointly optimize analytics
• Make data more reliable & understandable so products can adapt quickly to customer needs and requirements

Skills on Resume:

• Data Cleaning (Hard Skills)
• Version Control (Hard Skills)
• ETL Infrastructure (Hard Skills)
• Data Assembly (Hard Skills)
• Process Automation (Hard Skills)
• Tableau Reporting (Hard Skills)
• Collaboration (Soft Skills)
• Communication (Soft Skills)

Job Summary:

• Work on high impact projects that improve data availability and quality
• Provide reliable access to data for the rest of the business
• Analytics expert at the company
• Help bridge the gap between understanding business needs 
• Knowing how to design efficient, usable data models.
• Work with engineers, product managers
• Data analysts to understand data needs
• Build data expertise and own data quality
• Help define the data and analytics strategy 
• Technical direction, advocate for best practices
• Investigate new technologies
• Modeling data in a visualization tool like Power BI
• Working knowledge of using version control to create high quality code
• Manage data delivery projects where will plan tasks, set timelines, manage and update stakeholders, resolve blockers and drive the process forward

Skills on Resume:

• Data Modeling and Design (Hard Skills)
• Analytics Expertise (Hard Skills)
• Business Understanding (Soft Skills)
• Technical Proficiency (Hard Skills)
• Project Management (Soft Skills)
• Data Quality Assurance (Hard Skills)
• Strategic Thinking (Soft Skills)
• Continuous Learning (Soft Skills)

Job Summary:

• Work with stakeholders to design and deliver data solutions which provide them with the insight they need to make the right decisions
• Help build and support enterprise data warehouse.
• Help support Customer Data Platform, providing the right data to deliver timely communications across marketing channels
• Work alongside a talented team of Data Engineers, Data Scientists and business stakeholders
• Develop business, data and technical skills to tackle wider architectural concerns
• Developing a deep understanding of data pipeline, and its interaction with the business domain
• Collecting requirements, designing and delivering analytics solutions
• Building data pipelines and front-end frameworks
• Integrating data from internal and external systems
• Championing data quality
• Providing operational support for systems and processes
• Designing reports and dashboards and supporting users
• Ad hoc analysis, interpreting and communicating results
• Investigate solutions to new data-driven problems and tools to be developed in-house
• Research and evaluate new possible solutions for data-driven analysis and future Big Data developments

Skills on Resume:

• Collaboration and Teamwork (Soft Skills)
• Architectural Understanding (Soft Skills)
• Data Pipeline Management (Hard Skills)
• Analytics Solution Development (Hard Skills)
• Data Integration (Hard Skills)
• Data Quality Advocacy (Soft Skills)
• Operational Support (Soft Skills)
• Report and Dashboard Design (Hard Skills)

Job Summary:

• Drive value by ensuring timely, high-quality data is available to multiple user groups across the organization. 
• Design, build and deploy scalable, version-controlled ETL jobs that automate analytics processes. 
• Plan and manage large projects, setting priorities, and facilitating collaboration to ensure timely and accurate completion. 
• Identify emerging analytic needs of external and internal stakeholders and drive technical innovation to meet those needs. 
• Collaborate with and leverage the expertise of key partners from analytic, clinical, business, technical, and other teams in the development of new capabilities, processes, and deliverables. 
• Implement appropriate safeguards
• Maintain physical security and utilize appropriate technical controls
• Observe access rights & restrictions.
• Work with multidisciplinary teams for the development  
• Delivery of analytics solutions through agile methodology 
• Develop and manage skills in machine learning, statistical modeling, and other computational approaches  
• Extract insights from proprietary and public science data sources. 
• Establish and manage collaborations engaging business units 
• Develop novel data analytic approaches and integrated decision science solutions. 

Skills on Resume:

• Data Management (Hard Skills)
• ETL Automation (Hard Skills)
• Project Management (Hard Skills)
• Technical Innovation (Hard Skills)
• Cross-functional Collaboration (Soft Skills)
• Agile Methodology (Soft Skills)
• ML & Statistical Modeling (Hard Skills)
• Business Collaboration (Soft Skills)

Job Summary:

• Support and contribute to the analytics layer of team's data environment to make data standardized and easily accessible to end-users
• Integrate new data sources and build ingestion pipelines for data warehouse
• Write production-quality ELT/ETL data transformation code with an eye for performance, maintainability and scalability
• Help bridge the gap between understanding business needs and knowing how to design efficient, usable data models
• Diagnose and fix data discrepancies and maintain transparent code to ensure business requirements and consistent ETL logic
• Collaborate with stakeholders in growth marketing, merchandise planning, digital product, and finance & operations departments
• Define business questions and identify opportunities for data-driven improvements
• Build and maintain dashboards in Looker to deliver insights and help non-technical stakeholders be able to regularly track KPIs
• Document and communicate data insights and recommendations to stakeholders across the company and advocate for a data-driven culture internally and externally
• Provide strategic data and analytics support to develop and evaluate growth opportunities.

Skills on Resume:

• Data Integration (Hard Skills)
• Database Design (Hard Skills)
• Data Quality Management (Hard Skills)
• Stakeholder Collaboration (Soft Skills)
• Dashboard Development (Hard Skills)
• Communication (Soft Skills)
• Problem Solving (Hard Skills)
• Collaborative Leadership (Soft Skills)

Job Summary:

• Build and maintain the analytics layer of the team's data environment to make data standardized and easily accessible
• Maintain/build derived marketing/sales schemas on the Lamwork cluster and investigate and refactor any expensive queries
• Integrate third-party data sources as add channels, data partners and other vendors
• Working closely with Product and Engineering to ensure upstream product model changes integrate
• Define user roles and permission levels for Lamwork and BI tools
• Performing stakeholder-related work, such as dashboards or analysis
• Integrating and productionizing analyst and data science models.
• Build data expertise, best practices and own data quality for all analytical data needs
• Define and manage SLA for all data sets in allocated areas of ownership
• Coordinate collaborating of data science group across all of ADM  
• Develop solutions for meaningful business, financial, and operations questions in cross-functional teams

Skills on Resume:

• Data Architecture (Hard Skills)
• Database Optimization (Hard Skills)
• Data Integration (Hard Skills)
• Collaboration with Teams (Soft Skills)
• Access Control (Hard Skills)
• Stakeholder Communication (Soft Skills)
• Model Integration (Hard Skills)
• Data Governance (Hard Skills)

Job Summary:

• Demonstrate ability to influence change, define standards and apply software engineering best practices to cleans and transform data to enable data science and BI insights.
• Collaborate with Engineers, Business Analysts, Data Modelers, SMEs, and Data governance liaisons to achieve a very good understanding of metadata and data quality requirements and then deliver data fit for purpose to enable Business Intelligence insights.
• Support the delivery of self-serve analytics by translating information for use in natural language search-based tool sets.
• Explore and analyze large datasets, understand underlying data relationships, assess data quality, optimize table structures, identify data gaps/optimization opportunities.
• Promote and demonstrate SQL change management procedures.
• Support data strategies, policies, processes, and best practices.
• Collaborate with data stewards, architects, and engineers to support scrum/agile delivery.
• Deep working knowledge of relational databases and dimensional modeling
• Drive table design, transformation logic and efficient query development to support the growing needs of the data analytics organization.
• Build, develop and maintain data models, reporting systems, data automation systems, dashboards 

Skills on Resume:

• Influencing Change (Soft Skills)
• Collaboration (Soft Skills)
• Data Analysis (Hard Skills)
• SQL Proficiency (Hard Skills)
• Data Governance (Hard Skills)
• Agile Methodologies (Hard Skills)
• Relational Databases (Hard Skills)
• Data Modeling and Reporting (Hard Skills)

Job Summary:

• Performance metrics support that support key stakeholder decisions.
• Discover insights and drive opportunities for use of those insights into product offering
• Provide accurate estimations for development activities that drive sprint planning and release cycles.
• Staying abreast of the new feature/functionality that is available in the software(s) that CyberGrants leverages 
• Design and implement efficient data pipelines (ETLs) in order to integrate data from a variety of sources
• Design and implement data model changes that align with warehouse standards and make it easier for business teams to access and analyze data
• Develop and execute testing strategies to ensure high-quality warehouse data
• Provide documentation, training, and consulting for business users
• Perform data analysis and build reporting structures that support the view of the customer and product offering
• Build ML and AI models that help support the customer experience
• Work with cloud-based software and integrate with external systems to keep data flowing in and out of ecosystem

Skills on Resume:

• Data Analysis and Interpretation (Hard Skills)
• Insight Generation (Hard Skills)
• Estimation and Planning (Hard Skills)
• Software Proficiency and Continuous Learning (Hard Skills)
• ETL (Extract, Transform, Load) (Hard Skills)
• Data Modeling and Warehousing (Hard Skills)
• Testing and Quality Assurance (Hard Skills)
• Documentation, Training, and Consultation (Soft Skills)

Job Summary:

• Define, build and enhance integrated, enterprise-wide data architecture and data analytics solutions.
• Deliver a data analytics architecture that produces transparency and provides actionable, timely and accurate data to drive business, user experience and product strategy initiatives
• Provide data analytics services to internal stakeholders to help solve critical business problems, drive value, and gain strategy and insight from information.
• Use advanced data analysis techniques and architectures that leverage technology to process large volumes of data to perform complex computations in a scalable, reproducible and automated manner.
• Build upon a common data framework so that all data is accessible to analysts and data scientists throughout the company.
• Obsess about learning, and champion the newest technologies & tricks with others, raising the technical IQ of the team.
• Work with large sets of data to build data pipelines and analytics for executive and company wide reporting
• Work collaboratively with data engineers, analysts, and data visualization engineers to deliver analytic solutions.
• Be an energetic ‘self-starter’ with the ability to take ownership and be accountable for deliverables.
• Supporting the exchange of information and strengthening analytic capabilities in the production network, considering new technology trends and the experience of external technology experts and suppliers.

Skills on Resume:

• Data Architecture (Hard Skills)
• Data Analytics (Hard Skills)
• Problem Solving (Hard Skills)
• Advanced-Data Analysis (Hard Skills)
• Data Framework Development (Hard Skills)
• Continuous Learning (Soft Skills)
• Data Pipeline Development (Hard Skills)
• Collaboration and Accountability (Soft Skills)

Job Summary:

• Develop and support analytics platform
• Design and deliver data solutions, providing stakeholders with the insight they need to make the right decisions
• Work alongside a talented team of data and analytics engineers, data scientists, insight analysts and business stakeholders
• Develop business, data, and technical skills to tackle wider architectural concerns
• Developing a deep understanding of data pipeline and how it interacts with the business
• Collecting requirements and designing and delivering analytics solutions, such as data pipelines and front-end frameworks
• Integrating data from internal and external systems
• Championing data quality
• Providing operational support for systems and processes
• Designing reports and dashboards, and supporting users
• Development of use cases in the areas of Safety, Quality, Agility, Sustainability, Capacity and Efficiency to drive step changes in key processes, including the production, transport and storage of masses, the associated raw material and media supplies, cleaning and disposal technologies

Skills on Resume:

• Analytics Platform Development (Hard Skills)
• Data Solution Design and Delivery (Hard Skills)
• Team Collaboration (Soft Skills)
• Continuous Skill Development (Hard Skills)
• Data Pipeline Understanding (Hard Skills)
• Requirements and Solution Design (Hard Skills)
• Data Integration (Hard Skills)
• Data Quality Advocacy (Soft Skills)

Job Summary:

• Database and query optimization in SQL
• Data processing and task management in Python
• Technical communication, translating between domains with other engineering teams and non-engineering stakeholders
• Team-oriented development: building modular & re-usable tools, writing maintainable code, owning technical and business documentation
• SQL experience working with and optimizing complex queries on large datasets
• Writing code in Python 3 with comprehensive documentation and testing
• Proficiency on a command line, including processing data samples
• Software development lifecycle experience in GitHub (e.g. code review, testing, deployment)
• Containerized development using Docker, Kubernetes
• Delivering technical communication to audiences of diverse backgrounds
• Review existing big-data applications and architecture, identify and implement improvements, automating and optimising dataset creation and data delivery for greater scalability and reliability
• Own, monitor and manage data delivery systems, debugging and fixing any related issues
• Provide datasets and tools for data science team members that enable them to perform ad-hoc analysis, as well as build and optimise machine learning models
• Support data literacy within the team and company as a whole through a combination of mentoring, technical leadership, making others better by raising the bar

Skills on Resume:

• SQL Optimization (Hard Skills)
• Python Data Processing (Hard Skills)
• Technical Communication (Soft Skills)
• Team-Oriented Development (Soft Skills)
• SQL Expertise (Hard Skills)
• Python 3 Development (Hard Skills)
• Command Line Proficiency (Hard Skills)
• SDLC and Tools (Hard Skills)

Job Summary:

• Develop, maintain and improve data generation and ingestion pipelines
• Collaborate with marketers, data scientists, and analysts to develop, maintain and improve data ingestion pipelines
• Write standardized R or Python codes that are frequently needed for the team.
• Develop and maintain complex SQL queries
• Pull and join data from disparate sources and perform data transformations, in support of data science and analytics projects.
• Evaluate marketing technologies for their data-gathering capability
• Validate and consolidate diverse sources of data such as Salesforce.com, DialogTech, and Adobe
• Develop and maintain ML algorithms 
• Work with Data Scientists and Analysts to develop and maintain predictive models and machine learning algorithms, including marketing, pricing, and revenue management programs.  
• Create and maintain standard (daily, weekly or monthly) and ad hoc performance reports
• Conduct ad hoc analytic
• Perform ad hoc analysis to discover business insights to enhance marketing programs and optimize pricing systems
• Writing complex SQL queries against relational database systems.
• Developing and/or implementing machine learning algorithms

Skills on Resume:

• Data Processing Skills (Hard Skills)
• Collaboration (Soft Skills)
• Data Integration and Transformation (Hard Skills)
• Marketing Technology Evaluation (Hard Skills)
• Data Validation and Consolidation (Hard Skills)
• Machine Learning (ML) Skills (Hard Skills)
• Reporting and Analytics (Hard Skills)
• Ad Hoc Support (Hard Skills)

Job Summary:

• Design, develop, and maintain a scalable and extensible data model for the analytical needs of the business, incl. the data catalog
• Manage transformations of data either before or after a load of raw data through both technical processes and business logic
• Work closely with product, engineering, and business teams to gather business requirements
• Lead analytics initiatives with design and performance optimizations of data warehouses/Lakehouse
• Architect, implement & extend the capabilities of the self-service data platform
• Develop, maintain & optimize ETL & ELT pipelines
• Work with BI teams in triaging, prioritizing, and achieving their objectives
• Documenting, reporting and presenting data for key business decisions, such as KPIs and other requirements.
• Design solutions alongside the implementation process for the various applications to debug issues.
• Need to create customized analytic solutions and be able to communicate these results to key stakeholders.
• Work with multiple clients at once and remain organized to ensure projects are within scope.

Skills on Resume:

• Data Modeling (Hard Skills)
• Data Transformation (Hard Skills)
• Requirements Gathering (Soft Skills)
• Analytics Initiative Leadership (Hard Skills)
• ETL & ELT Pipeline Development (Hard Skills)
• Collaboration and Prioritization (Soft Skills)
• Data Reporting and Documentation (Hard Skills)
• Analytic Solutions & Communication (Soft Skills)

Job Summary:

• Work cross-functionally with Software Engineers, Product Managers, Sales and Services.
• Be responsible for developing Production-level commercial Analytics that leverage Statistical, Machine Learning and other techniques applied to Predictive and Prescriptive use cases on Industrial equipment and processes.
• Engage with Subject Matter Experts with an Engineering background to combine the physical world with the data of the digital world into a Digital Twin.
• Be adaptable and responsive to commercial needs as well as learning new industries and how various equipment and processes work.
• Apply a structured process for discovery, development, testing, and quality validation supported by Agile Framework and Software Development Lifecycle management.
• Provide data and algorithm specifications and requirements to software engineering on data-powered functionality.
• Plan, designed, developed, and maintained the data infrastructure for various analysis systems in support of core organizational functions and business processes.
• Combine analytics skills and an understanding of the processes and data that support organ and tissue donation, and healthcare EMR systems to inform the ongoing transformation of the organ procurement/transplant industry.
• Design, build and standardize big data architectures, large-scale data pipelines and deliver clean datasets for advanced analytics, as well as for AI and ML models together with data science team
• Work closely with Product teams to deliver the data required to fuel  products

Skills on Resume:

• Digital Twin Integration (Hard Skills)
• Adaptability and Learning (Soft Skills)
• Structured Development Process (Hard Skills)
• Communication Skills (Soft Skills)
• Data Infrastructure Management (Hard Skills)
• Industry Knowledge and Integration (Hard Skills)
• Big Data Architecture and Pipelines (Hard Skills)
• Collaboration with Product Teams (Soft Skills)

Job Summary:

• Deliver sustainable, effective, and efficient reporting and analytical solutions for the Customer Operations teams.
• Enable business insights by gathering functional requirements and developing user stories working directly with business stakeholders.
• Build and standardize data visualization across teams to enable consistency and quality control of key business data.
• Architect and model dashboards and user interactions based on business requirements.
• Participate in business intelligence reporting, governance, and process improvement by supporting a culture of intellectual curiosity and continuous learning and maintaining standards and documentation.
• Identify end-user training needs and work with them to resolve issues.
• Independently solve moderately complex issues with minimal supervision, while escalating more complex issues to appropriate staff.
• Collaborate with other Analytics Engineers in Cargill to leverage best practices and learn new technologies and techniques.

Skills on Resume:

• Data Analysis and Reporting (Hard Skills)
• Requirements Gathering and User Stories (Hard Skills)
• Data Visualization (Hard Skills)
• Dashboard Architecture and Modeling (Hard Skills)
• Business Intelligence and Governance (Hard Skills)
• End User Training (Hard Skills)
• Problem Solving (Hard Skills)
• Collaboration and Continuous Learning (Soft Skills)

• Support Manufacturing teams by turning data into critical information and knowledge that can be used to make sound business decisions.
• Conducts analyses of performance data and analytics program outputs to drive targeted problem solving and corrections on the plant floor.
• Analyzes data and discovers patterns, meaningful relationships, anomalies and trends.
• Identifies and provides input to new technology opportunities that will have an impact on the Manufacturing BI systems & processes.
• Utilize personal knowledge augmented with analytics-generated data to drive performance improvement in manufacturing systems.
• Works closely with the IT Data team in developing the data infrastructure to support data needs.
• Design, develop, and maintain data pipelines to enable faster business analysis and reporting.
• Manage automated unit and integration test suites to ensure data correctness and consistency.
• Maintain source code repository of scripts (SQL, Python/R) and other products (dashboards, reports, etc.).
• Partner with our product managers and finance teams to publish datasets for measuring key performance indicators
• Understand and document business processes and design a path to incorporate new initiatives into existing solutions