Job Description:

Position Description:

Conducts data analysis using Snowflake, SAS, SQL for data querying, Python, and Alteryx. Handles day-to-day planning, ensuring the team delivers high quality analytical projects. Designs and develops data templates for analytics capabilities. Plans the agenda for client presentations. Uses visualization tools to create dashboards – Power BI and Tableau. Promotes analytical capabilities developed within the team to use for other groups across the business.

Primary Responsibilities:

• Develops and delivers analytics capabilities for retirement plan sponsors.
• Develops data science pipelines in partnership with other teams.
• Develops and implements Artificial Intelligence (AI) / Machine Learning (ML) models.
• Develops analytics dashboards to help stakeholders assess Key Performance Indicators (KPIs).
• Collaborates with other teams across the business to develop the plan for the analytics strategy.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Information Management, Business Administration, or a closely related field and six (6) years of experience as a Director, Data Analytics and Insights (or closely related occupation) performing data analysis using Snowflake, SAS, SQL for data querying, Python, and Alteryx.

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Information Management, Business Administration, or a closely related field and four (4) years of experience as a Director, Data Analytics and Insights (or closely related occupation) performing data analysis using Snowflake, SAS, SQL for data querying, Python, and Alteryx.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) designing and developing analytical tools and frameworks for retirement plan and participant analytics — supporting workplace clients to assess the effectiveness of their plan design and make changes to improve the retirement outlook; conducting large scale quantitative and qualitative studies, and satisfaction and loyalty studies, and leading behavioral science experimentation, creating and driving segmentation, tracking consumer trends.
• DE managing and monitoring data platforms with data driven objectives — synthesize large sets of data and supporting data science pipelines.
• DE extracting marketing and customer data for analysis using structured databases — Snowflake and SQL/SAS; creating programmatic scripts to extract, transform, and manipulate data, using Python or R; and creating interactive marketing results dashboards using Business Intelligence (BI) tools — Power BI and Tableau.
• DE engaging with business partners to understand business objectives and challenges to identify analytic needs — developing strategic direction and providing innovative solutions for data analytics teams on delivery of projects and capabilities at scale.

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Certifications: