• Help create data analysis and analytics pipelines that improve not only the underlying ML algorithms but also the product and the user's experience. 
• Lead a team of Analysts
• Be responsible for good data-driven hygiene, including the creation, redesign, and maintenance of analytics dashboards and BI tools such as BigQuery, Google Data Studio, or Tableau. 
• Advise on data labeling strategy so that Woebot's conversational engine is continuously improved and informs changes in features, content, and UX. 
• Create and lead a data-driven personalization strategy for this audience. 
• Personalize is key for developing a relationship over time while delivering precision interventions, that are the right method to the right person at the right time. 
• Help develop evidence and trends to demonstrate the value of highest-priority products. 
• Helping answer the most pressing questions in the mental health field around engagement, dose, and treatment outcomes. 
• Contribute to the pipeline of peer-reviewed published research. 
• Lead publication in Data Science and HCI research. 
• Assess the lay of the landscape and team 
• Make suggestions around in-house analytic tools, dashboards and strategies. 

Skills: Data Analysis, Team Leadership, Analytics Pipeline Development, Data Hygiene Practices, Dashboard Maintenance, Data Labeling Strategy, Personalization Strategy, Research Publication

• Be responsible for advanced and predictive data analytics from complex and high-value projects using big data and data science technology for healthcare innovation and outcomes. 
• Be responsible for conducting complex statistical and algorithmic data analyses and the development of technologies to improve the health of members. 
• Lead data analytics challenges in organization, collecting large volumes of data from varying sources
• Working with Data Scientists to clean and interpret data, create solutions to overcome challenges and communicate with interested parties. 
• Build an environment across Data Scientists who are hungry to stay up to date on the latest technologies and practices. 
• Set the standard of being curious in solving the most complex problems and leading the vision of opportunities for improvements
• Working in a collaborative environment with other Leads, Developers, Product Managers and Experience Designers. 
• Design and develop analysis tools that extract, prepare, and analyze data and store analytical results for downstream analysis and reporting for business needs 
• Build key data sets to empower operational and exploratory analysis and designing and evaluating experiments monitoring key product metrics, understanding root causes of changes in metrics 
• Develop tools to convert unstructured data to partially or fully structured representations as well as process large sets of data to derive statistical information. 
• Apply expertise in quantitative analysis, data mining, and the presentation of data to understand how users interact with business products 
• Develop mathematical and statistical models for distinguishing relevant from irrelevant content or events. 

Skills: Predictive Data Analytics, Statistical Analysis, Data Cleaning and Interpretation, Data Environment Leadership, Collaborative Problem Solving, Analysis Tool Development, Unstructured Data Processing, Quantitative Analysis

• Participate in developing presentations and communicate the results of research analysis and findings. 
• Participate in the design of automated, operational analytics processes to achieve scale and durability of analysis processes. 
• Measure and validate the outcomes of health management programs using SAS, R and other tools, including provider data, claims data, membership data, etc. 
• Coordinate analysis and development initiatives and capabilities with health plans. 
• Manage multiple projects as assigned and assist with training Data Analysts. 
• Be responsible for development efforts with technical team liaisons, including gathering business requirements, documentation, testing, delivery and user adoption
• Communicate expectations to the Health Plan.
• Understand the roadmap with the founder and reverse engineer tailored interventions. 
• Deliver a prioritized list of roadmap items.
• Execute a plan for improving user outcomes with analytics and ML.

Skills: Research Presentation, Automated Analytics Processes, Outcome Measurement and Validation, Project Coordination, Data Analyst Training, Technical Development Liaison, Stakeholder Communication, User Outcome Improvement

• Hand-on development and coding of novel machine learning, statistical analysis, and operations research models.
• Build and prototype analysis pipelines iteratively to provide insights at scale.
• Collaborate with software engineering, product, and operations teams to understand company needs and propose possible solutions.
• Develop comprehensive knowledge of Beacon data structures and metrics, identifying and advocating changes where needed.
• Serve as the lead data expert and statistician on the APS project.
• Managing the APS data universe, determining areas of error
• Implement strategies for data improvement
• Analyzing, interpreting, and reporting on APS & vendor data regarding data quality and optimization of data translation efficiencies.
• Evaluating new APS vendors and potential data sources (both government and private industry supplied) to advise the Government on data acquisition strategy and cost-to-benefit ratios.
• Participating as the data SME on cross-project strategies involving Provider Screening & Enrollment data
• Providing expertise in screening, enrollment, and claims data to advise the Government on making informed data-driven business decisions.
• Use a variety of industry-accepted tools, standards and methodologies in mathematics and statistics to determine both data quality strategies and analysis.

Skills: Machine Learning Development, Analysis Pipeline Prototyping, Cross-Functional Collaboration, Data Structure Knowledge, Data Quality Management, Data Improvement Strategies, Vendor Evaluation, Statistical Analysis Expertise

• Be a thought partner for the Pricing & Performance Manager and Sales leadership in unlocking the power of data & analytics to understand better markets, customers and business offerings
• Help build the foundation of a strong analytical and data science engine in the pricing and commercial organization
• Support the development and implementation of the pricing strategy
• Support the creation and regular update of Price price-setting algorithm with data insights, and analysis of market data (i.e. competitor data and historical pricing levels, service levels, value insights, etc.)
• Support commercial teams by providing and presenting commercial intelligence and performance insights for decision-making by collecting, organizing and analyzing data from different internal and outside systems
• Perform research and build a core understanding of customer performance metrics to qualitatively inform and interpret models.
• Work on interdisciplinary projects, using mathematics, econometrics, statistics, and machine learning to derive structure and knowledge from raw data across internal and external sources
• Be the process and value owner for pricing tools and platforms. taking the end-to-end responsibility (problem identification, data mapping, data preparation, modeling, and implementation) for data-related projects
• Interact with many stakeholders and a variety of departments, including sales, innovation, marketing, customer service, finance and supply chain
• Utilize Machine Learning and Data Mining to drive innovation
• Champion the team's operations

Skills: Data Analytics, Pricing Strategy, Market Analysis, Commercial Insights, Performance Metrics, Project Collaboration, Tools Management, Machine Learning

• Experience providing advanced analytics solutions
• Prior experience working with large quantitative and qualitative datasets
• Experience with programming languages such as Python, R, and VBA, and query languages such as SQL
• Experience with data visualization tools (e.g., Tableau, Qlik, Power BI)
• Proficiency with data extraction, transformation, and loading to support advanced analytics
• Experience with a wide range of analytics techniques, such as statistics, machine learning, natural language processing, optimization, simulation, or closely related techniques
• Ability to use appropriate methodology and approach for data science solutions to business problems
• Familiarity with cloud computing technology
• Must have strong collaboration skills
• The ability to excel in a fast-paced environment

Qualifications: BS in Mathematics with 4 years of Experience

• Prior banking or financial services experience.
• Knowledge of Actimize fraud monitoring solutions or equivalent platforms
• Excellent programming skills in one of the following tools - Python, R, SQL, and other tools.
• Knowledge of Tableau or PowerBI, able to visualize results using data visualization tools to make your conclusions more understandable to your audience.
• Analytical aptitude, critical and strategic thinking.
• Able to determine the optimal analytic and strategic approach for the development of Fraud strategies to mitigate fraud loss and improve fraud detection processes.
• Able to analyze results and make recommendations for key business partners and senior management or communicate conclusions from complex strategic solutions to a wide range of audiences.
• Knowledge and experience with ETL, Data warehouse, Hadoop, Teradata, Tableau
• Excellent written and verbal communication, business analysis, and consultancy skills
• Strong interpersonal skills with the ability to lead client projects and establish requirements in non-technical language.

Qualifications: BS in Computer Science with 5 years of Experience

• Combined data science and engineering experience with at least three of those on a machine learning team, with a track record of putting models into production and growing individual responsibilities
• Must be expert-level SQL
• Insatiable curiosity and analytical bent 
• Strong Python experience - experience writing code in a production environment
• Expert-level knowledge of data science libraries such as pandas, numpy, tensor-flow/keras or pytorch, sci-kit-learn, plotly (or equivalent)
• Strong familiarity with a gamut of data science and machine learning approaches, including neural networks, random forest and GBTs, KNNs, k-means clustering, various types of regressions, and Bayesian techniques
• Ability to function in a “big data” environment including an intermediate to expert knowledge of Spark or the ability and interest to quickly learn it on the job
• Familiarity with the AWS ecosystem and tools such as Glue, SageMaker, Athena, and Fargate
• Familiarity with Docker or other container systems
• Intelligence, humility, candor, and the ability to thrive in a fast-paced environment

Qualifications: BS in Applied Mathematics with 7 years of Experience

• A strategic and innovative thinker who is agile and possesses leadership capability.
• Experience with SQL and database skills in Teradata, and/or SQL Server databases.
• Strong Microsoft Office skills --Word, Excel, PowerPoint, Visio.
• Proficiency in R, Python and/or other complex analytical tools
• Experience in training and mentoring junior members of the team.
• Experience in analyzing data and providing recommendations.
• Client service and/or consulting experience
• Ability to infer complex code and make changes as necessary to adjust to the changing business needs.
• Ability to validate data and verify data marts built to adhere to business needs.
• Experience with both technical and non-technical presentation of analytic results.

Qualifications: BS in Data Science with 6 years of Experience

• Strong experience working with Python or R programming languages
• Experience working with data manipulation, analytic/business insight tools, and data visualization experience
• Experience with SciPy stack or Tidyverse packages
• Experience constructing and performing complex database search queries
• Experience/knowledge of computer science concepts, data architecture, and experience/knowledge of statistics
• Demonstrated experience using statistical and machine learning techniques including supervised and unsupervised learning and natural language processing
• Experience /familiarity with frequentist statistics and probability including predictive modeling
• Must have strong attention to detail.
• Ability to work effectively with cross-functional teams to perform planning and execution of initiatives.
• Ability to be flexible in a changing work environment,  and work well under pressure
• Experience working with digital marketing tools like Adobe Audience Manager, Liveramp and Invoca 

Qualifications: BS in Statistics with 8 years of Experience