Analytics Data Scientist (hybrid)

This work spans areas such as digital experience analytics, customer feedback and sentiment analysis, digital usage forecasting, member behavior modeling, feature adoption measurement, and operational optimization, helping drive better decisions, improve member outcomes, and enhance the digital experience for millions of members. • Experience applying analytical and statistical methods such as exploratory data analysis (EDA), hypothesis testing, regression, forecasting, segmentation and clustering, experimentation, NLP, or sentiment analysis to real-world business problems.

Analytics Data Scientist
Location: Vienna, VA (hybrid)
Pay Rate: Open to Both C2C and W2 options
Position Type: Contract

Description:
Our Digital Data Science & Analytics team is focused on understanding and improving the digital experiences of our members. Through analytics and applied data science, we uncover insights, inform strategic decisions, and enhance digital experiences and operations across the organization.
We are seeking a motivated customer-experience-focused analytics professional who is passionate about solving real-world business problems through data. This role is ideal for someone who enjoys combining exploratory analysis, statistical methods, experimentation, behavioral analytics, and fit-for-purpose modeling techniques to uncover insights and drive measurable impact.
As a member of our team, you will collaborate with cross-functional partners across product, technology, and business teams to transform complex questions into actionable insights. Our team draws from a broad range of analytical and data science techniques to deepen understanding of member behavior and digital experiences. This work spans areas such as digital experience analytics, customer feedback and sentiment analysis, digital usage forecasting, member behavior modeling, feature adoption measurement, and operational optimization, helping drive better decisions, improve member outcomes, and enhance the digital experience for millions of members.

Qualifications:
• Bachelor’s degree in data science, business analytics, statistics, applied mathematics, economics, or another quantitative or analytical field
• 1-5 years’ experience conducting data science, business intelligence, analytics, statistical analysis, or related project work
• Proficiency using SQL for data extraction and analysis and Python for data preparation, exploratory analysis, statistical analysis, and modeling; experience with R is beneficial
• Experience applying analytical and statistical methods such as exploratory data analysis (EDA), hypothesis testing, regression, forecasting, segmentation and clustering, experimentation, NLP, or sentiment analysis to real-world business problems
• Experience translating analytical findings into insights, recommendations, or measurable business outcomes for technical and non-technical stakeholders
• Comfort working in notebook-based analytical environments
• Strong curiosity and ability to learn new analytical methods and technologies quickly
• Excellent communication and data storytelling skills

Desired Qualifications:
• Master’s degree in data science, business analytics, statistics, applied mathematics, economics, or another quantitative or analytical field
• Experience analyzing customer behavior, digital products, customer feedback, or customer experience
• Experience presenting complex analyses to executive audiences with decision-support materials
• Knowledge of financial services or digital banking products
• Advanced SQL and Python skills

Responsibilities:
• Analyze member digital behavior using Python and SQL
• Conduct exploratory data analysis to identify patterns in product adoption, engagement, and customer experience
• Partner with business stakeholders and product teams to solve digital experience challenges
• Develop, automate, and maintain analytical solutions that provide actionable business insights
• Apply analytical and statistical methods to understand customer behavior, evaluate digital experiences, identify emerging trends, and support data-driven business decisions
• Apply text analytics, NLP, and AI-assisted techniques to summarize and classify customer feedback, identify sentiment and recurring themes, and surface customer friction points
• Analyze app reviews, surveys, contact center interactions, social media, and other digital feedback sources to conduct Voice of the Customer (VoC) and Voice of the Member (VoM) research
• Translate analytical findings into clear recommendations, dashboards, presentations, and data stories for business and executive audiences

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Ref: #851-Rockville-S1