Senior Data Scientist

About This Position

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.

Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision‑makers should be matched to Business Intelligence.

Incumbents whose primary role is technical and focused on designing and building system‑generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics. Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data.

Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate. May be internal operations‑focused or external client‑focused, working in conjunction with Professional Services and outsourcing functions.

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.

Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision‑makers should be matched to Business Intelligence.

Incumbents whose primary role is technical and focused on designing and building system‑generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics. Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data.

Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate. May be internal operations‑focused or external client‑focused, working in conjunction with Professional Services and outsourcing functions.

• Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems.
• Mentor and guide junior data scientists, fostering a culture of excellence and continuous learning within the team.
• Collaborate with cross‑functional teams (engineering, product, business stakeholders) to define data science project…