Senior Data Scientist - Experimental Design

Senior Data Scientist - Experimental Design

We seek a Senior Data Scientist (Experimental Design) to join our client's Data Science Lab in a Hybrid role (2 days a week in Office). This is a Direct Hire opportunity.

Hybrid Office locations: New York, Holmdel, Stamford, Bethlehem, Pittsfield

Your Job

As a Senior Data Scientist, you will be responsible for developing advanced data science solutions leveraging machine learning and artificial intelligence to drive enterprise-wide innovation. You will collaborate with senior executives on high-impact, high-visibility projects to deliver AI/ML solutions and create value from our data and analytic products. Your responsibilities will include developing test and learn capabilities, designing and executing experiments, creating statistical and AI/ML models, and conducting A/B testing.

The Work

• Develop Enterprise Test and Learn Capabilities
• Investigating the current state of the art of experimentation practices and causal inferencing/ML techniques to identify opportunities for upscaling the methodology best practices
• Develop and execute advanced data-driven experiments to optimize various aspects of client’s business
• Create test hypothesis, experiment design including KPI selection, and collect and analyze data
• Develop statistical and AI/ML models to analyze experimental data and derive actionable insights
• Apply statistical methods to assess the reliability and significance of experimental results
• Conduct A/B testing, multivariate tests, and other experimental methodologies to optimize customer experience, product features, marketing campaigns, and other business objectives
• Organize and manage data to extract insights that can be further incorporated into solution/model • Support use case development that includes initial data exploration, project/sample design, reception and processing of data, performing analysis and modeling to creation of final report/presentation
• Data wrangling/data matching/ETL to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets
• Utilize advanced statistical and AI/ML techniques to create high-performing predictive models and creative analyses to address business objectives and partner needs
• Identify source data and data quality checks both in model/solution development and in production
• Package model/solution and deployment in cooperation with Data Engineers and MLOps
• Develop Deep Learning/Large Language Model/Generative AI capabilities
• Map and mine unstructured data such as insurance contracts, medical records, sale notes, and customer servicing logs
• AI/ML solutions include but not limited to enhancing underwriting risk assessment, claims auto adjudication, and customer servicing
• Contribute to the overall Data Science organization
• Collaborate with cross-functional teams of other Data Science, Data Engineering, Business groups
• Contribute to standardization of Data Science tools, processes, and best practices

Qualifications

• Combination of education in Statistics, Computer Science, Engineering, Applied mathematics or related field AND professional experience in Data Science or Data Analysis equaling either:
• PhD with 2+ years professional experience
• Master's degree with 4+ years professional experience
• 3+ years of hands-on ML modeling/development experience
• Strong theoretical foundations in probability & statistics, and causal inferencing techniques
• Proven expertise in setting up hypotheses to assess consumer behavior, in designing, implementing and deploying tests
• Strong programming skills in Python including PyTorch and/or Tensorflow
• Solid background in algorithms and a range of ML models
• Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level
• Excellent analytical and problem-solving abilities with superb attention to detail
• Proven leadership in providing technical leadership and mentoring to data scientists and strong management skills with ability to monitor/track performance for enterprise success

Nice to Have

• Experience in the insurance industry
• Experience with big data technologies such as Hadoop, Spark, and/or cloud computing
• Knowledge of Agile development methodology
• Experience with data visualization tools such as Tableau, QlikView, and/or D3.js

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