Job Summary: 

• Taking projects from the initial business case into detailed scoping and delivery of each analytics product
• Owning projects through delivery, ensuring time, cost/benefits, and quality of solutions are managed
• Establishing simple and effective governance with each product/business owner to ensure effective management of expectations and outcomes
• Leading a small team of data scientists and data engineers to design and build each analytics product
• Utilize internal solutions along with third-party vendor applications and where relevant, open source algorithms, continually scanning the market for innovative analytics and data science capabilities that could benefit business and clients
• Utilising the cloud analytics platform and ensuring future product needs are accommodated in the development roadmap
• Evangelize the use of Stock Modelling to promote the development
• Communicating with technical and non-technical stakeholders
• Define and drive analytic agenda, finding and prioritizing the most impactful opportunities to improve business and customer experience
• Working with team of data scientists to develop comprehensive analytic plans and execute analytic projects
• Work with cross-functional partners to establish new operating models, establish new solutions, and drive organizational change
• Find, screen, and work with external vendors who can provide data we do not have access to internally to improve analytic capabilities

Skills on Resume: 

• Project Management (Hard Skills)
• Team Leadership (Soft Skills)
• Stakeholder Communication (Soft Skills)
• Data Analytics (Hard Skills)
• Vendor Management (Hard Skills)
• Cloud Computing (Hard Skills)
• Change Management (Soft Skills)
• Market Research (Hard Skills)

Job Summary: 

• Understand product, risk, and business requirements and how to apply ML to solve the most challenging problems in impactful ways
• Creatively leverage new and existing data to increase the effectiveness and efficiency of decision-making infrastructure
• Partner with ML engineers to design machine learning solutions that operate quickly and effectively at scale
• Make business recommendations to the executive and cross-functional teams (e.g. cost-benefit, forecasting, experiment analysis) effectively through presentations of findings and visualizations of quantitative information
• Lead efforts to build the next generation of data products at Chime
• Feature Engineering to prepare data sets as available from acquisition pipeline, ontology and graph to build robust models
• Build a differentially private federated learning system for all current and future ML models to ensure training data is protected and remains local while models are globally available
• Ensure models are explainable and unbiased using open-source libraries while looking at opportunities to augment them to fit needs
• Use expertise to advise delivery teams engaged in projects with big pharma.
• Developing advanced machine learning algorithms and statistical models to solve critical problems and help deliver the best customer experiences. 
• Partners with Business teams, the Platform team, the Security team, and other stakeholders to implement data science models into live production systems. 
• Brings fresh perspectives to inform decision-making toward better player experience by translating player voice into insights.

Skills on Resume: 

• Machine Learning (Hard Skills)
• Data Visualization (Hard Skills)
• Feature Engineering (Hard Skills)
• Statistical Modeling (Hard Skills)
• Cross-Functional Collaboration (Soft Skills)
• Data Privacy (Hard Skills)
• Business Analysis (Hard Skills)
• Problem Solving (Soft Skills)

Job Summary: 

• Using Python and Postgresql (and on occasion Excel) for user-level data analysis
• Working with data warehouse, specifically through MODE and HEAP analytics
• Working within the Data Team and alongside development teams to better scale data collection of relevant product and user data points
• Assisting in building necessary data infrastructure to continue to expand analysis capabilities
• Analyzes data, as well as contributes to the design, implementation, and delivery of analytics products and services.
• Builds predictive models, tools, and data visualizations.
• Oversees and/or leads research development projects and data science project plans for clients and internal initiatives.
• Drive the selection of innovative technologies to solve problems that nobody yet could solve. 
• Develop machine learning models to structure and analyze scientific data
• Use NLP and statistical models to classify data
• Collaborate with data quality teams to define training sets and metrics
• Verify that the outcomes meet the acceptance criteria

Skills on Resume: 

• Python Programming (Hard Skills)
• Data Analysis (Hard Skills)
• Predictive Modeling (Hard Skills)
• Data Visualization (Hard Skills)
• Machine Learning (Hard Skills)
• Natural Language Processing (Hard Skills)
• Collaboration (Soft Skills)
• Research Development (Soft Skills)

Job Summary: 

• Understanding business challenges and creating valuable actionable insights
• Perform analysis using statistical and ML methods for predictive analytics, classification, clustering and regression.
• Clean, manage, and structure data from disparate sources
• Help transition from development environment to production
• Consider how the models will work at the terminal scale
• Collaborate with engineering teams to implement models
• Lead and take full responsibility over an initially small team, with a vision for team growth
• Envision, create, and execute a Data Science roadmap
• Collaborate with business, analytics, product, and engineering teams to gather requirements, and design data science models in various arenas 
• Lead the process to build, test, train, deploy and iterate production quality machine learning model artifacts that run in batch as well as real-time
• Work with data engineers to build solid data pipeline input into data science models
• Develop an expert-level understanding of business models and operations, and innovate to advance business through machine learning

Skills on Resume: 

• Predictive Analytics (Hard Skills)
• Data Cleaning (Hard Skills)
• Model Implementation (Hard Skills)
• Team Leadership (Soft Skills)
• Data Science Roadmap (Hard Skills)
• Collaboration (Soft Skills)
• Machine Learning (Hard Skills)
• Data Pipeline Development (Hard Skills)

Job Summary: 

• Collaborate with AO leaders, staff & business stakeholders from clinical, operational, financial and technical areas to gather, define and analyze requirements as well as design and implement robust reporting/analytic solutions to generate clinical, operational and financial insights
• Design, develop and pilot/ deploy state-of-the-art, data-driven optimization algorithms, forecasting and predictive/descriptive models beyond current PHS analytics capabilities to solve business problems using the latest and most appropriate technologies in statistical modeling and machine learning
• Conduct risk identification and mitigation planning and inform analytical senior leadership of any issues/escalations & risks
• Conduct design, modeling, statistical analyses and data visualization for both exploratory and hypothesis-driven data studies using clinical, financial, and administrative data sources
• Develop, test and validate both existing and new analytical prototypes, algorithms, models, methods, and data processes to support business decision-making as well as clinical and operational process improvement
• Analyze and model structured data and implement algorithms to support analysis using advanced data-driven analytical methods from statistics, data mining, econometrics, and operations research
• Perform advanced analytics techniques to mine unstructured data, using methods such as document clustering, topic analysis, named entity recognition, and document classification
• Perform exploratory data analysis, generate and test working hypotheses, and uncover historical trends and relationships using clinical, financial, and administrative data sources
• Support design, test and deployment of optimization algorithms, forecasting and predictive models for patient-level outcomes, utilization management, and overall medical services
• Support design, test and deployment of population scoring, stratification and segmentation based on predicted risk of adverse utilization/clinical and financial outcomes

Skills on Resume: 

• Requirement Analysis (Soft Skills)
• Statistical Modeling (Hard Skills)
• Risk Mitigation (Soft Skills)
• Data Visualization (Hard Skills)
• Predictive Analytics (Hard Skills)
• Advanced-Data Analysis (Hard Skills)
• Machine Learning (Hard Skills)
• Exploratory Data Analysis (Hard Skills)

Job Summary: 

• Work with the Head of the Department to scope out a vision for the Data Science practice within this multi-national organization.
• Liaise with internal stakeholders across the business to propose a PoC for the function.
• Build toward managing a team of Data Scientists.
• Application of Deep Learning for specific use around Customer Science.
• Manage and collaborate with another analytics stakeholder to define and pilot prototype BI tools
• Design and develop reusable analytical assets (data structures, code, solutions), recommend improvements to existing assets, and evaluate the suitability and value of potential new assets
• Train and manage analytical talent on the appropriate use and interpretation of new analytical models
• Facilitate integration of these models into existing business analyses as well as assure
• Maintain and improve efficiency and quality, validate work product of peers & junior scientists
• Established track record of presentations/publications and thought leadership in the AO area
• Contribute to developing a year-end value story to demonstrate the value of the team and their contribution to progress towards the AOs and PHSs goals.

Skills on Resume: 

• Team Management (Soft Skills)
• Deep Learning Application (Hard Skills)
• Stakeholder Engagement (Soft Skills)
• Prototype Development (Hard Skills)
• Analytical Asset Development (Hard Skills)
• Talent Training (Soft Skills)
• Quality Assurance (Hard Skills)
• Thought Leadership (Soft Skills)

Job Summary: 

• Manage relationships with external data science partners
• Improve the quality and integrity of the data
• Drive operational efficiency through increased automation of data capture
• Explore and introduce new data sets
• Build analytic systems and predictive models
• Test performance of data-driven products
• Visualize data and create reports
• Identify proper data sources necessary for projects and ensure they are accurately imported and joined. 
• Create an execution plan and assist data scientists in their efforts to implement.
• Identify proper analytic methodology and ensure analytic efforts are executed correctly. 
• Create execution plans and assist data scientists in efforts to implement.
• Ensure all projects have proper documentation taking into account potential regulatory, legal, or business concerns

Skills on Resume: 

• Relationship Management (Soft Skills)
• Data Quality Improvement (Hard Skills)
• Operational Efficiency (Hard Skills)
• Predictive Modeling (Hard Skills)
• Data Visualization (Hard Skills)
• Project Documentation (Hard Skills)
• Methodology Identification (Hard Skills)
• Execution Planning (Hard Skills)

Job Summary: 

• Provide direction, training and growth opportunities to data scientists on the team
• Collaborate with highly experienced engineers, data scientists, data engineers, and domain experts to develop well-defined problem statements for high-impact problems
• Develop sophisticated algorithms, automated processes, and software using large datasets from multiple disparate sources
• Collaborate with peers globally to establish Best Known Methods (BKMs) for standards, efficiency, and deployment
• Use in-depth data science expertise to influence the data science lifecycle
• Develop and deploy end-to-end data science solutions from the idea generation phase, PoC development to full productization.
• Drive actions and business impact through effective data presentation and data storytelling
• Fully lead data scientists functionally, including division of tasks/resources across projects and ensuring data scientists are productive and grow.
• Lead communication of project results/challenges to business partners in ways they can understand. 
• Proactive communication of delays to planned efforts.
• Ensure project tasks are fully planned, including understanding how implementation affects other units, how to measure results, how to achieve the expected benefit, etc.
• Identify and propose new technologies and tools that could benefit the Data & Analytics team.

Skills on Resume: 

• Team Development (Soft Skills)
• Algorithm Development (Hard Skills)
• Collaboration (Soft Skills)
• Data Science Expertise (Hard Skills)
• Data Storytelling (Soft Skills)
• Project Management (Hard Skills)
• Communication Skills (Soft Skills)
• Technology Innovation (Hard Skills)

Job Summary: 

• Lead a team of data scientists, offering coaching and development guidance
• Engage with key partners across different levels of the business to drive value outcomes from data science projects.
• Work with Subject Matter Experts and other business partners in Finance and Technology, to translate business problems into data science problems and to devise solutions, with measurement frameworks for key KPIs.
• Implement a highly visual and commercial approach when delivering data science projects that engage and challenge the thinking of non-technical audiences.
• Build production data science products by promoting robust software development standards and practices within teams, including testing and code reviews.
• Help drive the development of a high-functioning organization through the deployment of cutting-edge computational techniques applied to a wide range of data, including structured and unstructured healthcare data sources, patient-generated data, and complementary real-world information streams.
• Manage end-to-end data science projects, including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Provide operational and scientific support on multiple projects with a core role in delivering expertise in machine learning, modeling, simulation, and NLP/text mining on real-world data across Sanofi.
• Work with developers, engineers, and MLOps to deliver robust and scalable machine learning solutions.
• Contribute to the design, development, and implementation of Sanofi’s data science architecture and ecosystem to guide decision-making and building of foundational capabilities.
• Maintain internal and external profile through contributions to congresses and publications.

Skills on Resume: 

• Team Leadership (Soft Skills)
• Stakeholder Engagement (Soft Skills)
• Data Translation (Hard Skills)
• Project Management (Hard Skills)
• Software Development Standards (Hard Skills)
• Machine Learning Expertise (Hard Skills)
• Communication Skills (Soft Skills)
• Data Science Architecture (Hard Skills)