Data Scientist specializing in customer strategy and advanced analytics, with expertise in forecasting, leading end-to-end workstreams, driving strategic initiatives, and designing data-driven features. Regularly presents insights and recommendations to stakeholders and leadership teams.
Must haves:
- 5+ years of experience in data science, advanced analytics, and statistical modeling
- Strong SQL skills, including the ability to query complex datasets, transform data, and build analytical data models as needed
- Well versed in statistical modeling development and forecasting
- Proficiency in Python with hands-on experience applying it to data analysis, statistical analysis, and modeling
- Experience applying statistical techniques such as hypothesis testing, regression, forecasting, segmentation, or other quantitative methods in business settings
- Experience building analytical approaches that are methodologically sound, reproducible, and scalable
- Experience with data management, data wrangling, and exploratory analysis across large and complex datasets
- Experience using BI or data visualization tools (PowerBI)
- Agentic AI tooling experience- Claude, Cursor, etc.
Pluses:
- Experience designing experiments or using causal inference or other advanced measurement approaches to evaluate business initiatives
- Experience with customer analytics, retention, personalization, lifecycle, or marketing measurement
Day to day:
An employer is looking for a Data Scientist to focus on Customer Strategy & Advanced Analytics to help drive high-impact, data-led decision making across the organization. You will sit on the Customer Strategy & Advanced Analytics team and applies rigorous analytics, statistical methods, and modeling to solve complex business problems using data from across the organization.
The Analytics team brings the power of our extensive data assets and capabilities to the client’s most important decisions. In this role, you will partner closely with cross-functional stakeholders to identify opportunities, frame business questions, build robust analytical approaches, and translate findings into clear, actionable recommendations. The ideal candidate combines strong statistical judgment, technical depth, and business acumen, and is motivated by turning complex data into practical decisions that drive customer and business impact.
Responsibilities:
- Collaborate closely with cross-functional teams to identify business opportunities and translate ambiguous questions into structured analytical problems
- Build, validate, and maintain analytical and predictive models to better understand customer behavior, business performance, and strategic opportunities
- Conduct deep-dive analyses across multiple business domains to uncover drivers of performance, diagnose issues, and quantify opportunities
- Apply statistical methods and analytical rigor to evaluate business performance, test hypotheses, and support decision making
- Design and assess experiments, measurement frameworks, and other analytical approaches to estimate impact and separate signal from noise
- Develop scalable analytical frameworks, metrics, and data models that enable timely, repeatable, and decision-ready insights
- Communicate findings, assumptions, limitations, and recommendations clearly to both technical and non-technical stakeholders
- Build presentations and executive-ready materials that explain analytical conclusions and influence business action
- Partner with stakeholders to improve reporting, measurement, and analytical tooling in support of strategic decision making