Principal Data Scientist- Decisioning
Candidate Experience site · United States · Hybrid
Strong hiring record · median 41 days open
All reasons
In its favour
- Publishes a salary range
The Enterprise Data & Analytics organization is seeking a Principal Data Scientist to design, build, and improve quantitative models that strengthen customer relationships, improve decision quality, and drive measurable business outcomes.
In this role, you will
- Lead the development of statistical, machine learning, and causal inference solutions from problem definition through deployment, monitoring, validation, and continuous refinement.
- Evaluate targeting and decision performance using experimentation, counterfactual analysis, quasi-experimental techniques, and observational data to improve customer and business outcomes.
- Develop methods that estimate incremental impact, treatment effects, and heterogeneous customer response to support more effective and economically sound decisions.
- Translate ambiguous business objectives into defensible analytical problems, measurable outcomes, analytical requirements, and practical implementation plans.
- Partner with data science, marketing, product, finance, risk, data, and technology teams to integrate models into governed business processes and production decision systems.
- Synthesize analytic findings into a clear and approachable story and set of recommended actions, reducing complexity as appropriate for different audiences.
- Communicate assumptions, tradeoffs, limitations, and recommendations clearly while maintaining appropriate documentation, controls, and ownership.
- Guide the continuous improvement of analytical systems by incorporating experimental results, operational outcomes, and observed customer behavior into future models and targeting strategies.
A successful incumbent will have
- Master’s degree in statistics, economics, engineering, computer science, or a related quantitative field; PhD preferred.
- 10+ years of experience applying advanced analytics and delivering models through the full development lifecycle, including deployment, monitoring, governance, and ongoing improvement.
- Deep knowledge of statistical modeling, causal inference, and experimental design, with a demonstrated ability to improve decision quality and targeting through estimation and counterfactual reasoning.
- Experience estimating heterogeneous treatment effects and incremental value using randomized experiments, causal machine learning, quasi-experimental techniques, uplift modeling, and contextual bandits to support customer-level personalization and decisioning.
- Experience designing, executing, and evaluating experiments, including randomization strategy, holdouts, guardrails, outcome measurement, and causal interpretation of results.
- Strong Python and SQL skills (with 5+ years of applied experience each), including experience building reproducible analytical pipelines and working efficiently with large, complex datasets.
- Experience with cloud computing platforms (preferably AWS) and ML-related services such as Amazon Sagemaker.
- Ability to balance analytical rigor, interpretability, implementation complexity, and business usefulness under evolving priorities.
- Strong stakeholder-management and communication skills, including the ability to explain complex analytical, experimental, and causal concepts in clear, unambiguous language.
- Financial services experience and familiarity with related customer-level behavior, profitability, personalization, and relationship analytics preferred.
Hours & Work Schedule
- Hours per Week: 40
- Work Schedule: Monday - Friday
- Hybrid: 4 days per week onsite and 1 day remote
Pay
Transparency
The salary range for this position is $149,000 - $194,000 per year, plus an opportunity to earn an annual discretionary bonus. Actual pay is based on various factors including but not limited to the budget, work location, and relevant skills and experience.
We offer competitive pay, comprehensive medical, dental and vision coverage, retirement benefits, maternity/paternity leave, flexible work arrangements, education reimbursement, wellness programs and more. Note, Citizens’ paid time off policy exceeds the mandatory, paid sick or paid time-away policy of every local and state jurisdiction in the United States. For an overview of our benefits, visit https://jobs.citizensbank.com/benefits .
Skills
- Agility
- Building Relationships
- Business Data Analysis
- Business Savvy
- Critical Thinking
- Customer Empowerment
- Diversity and Inclusion Practice
- Industry Insight
- Innovation
- Machine Learning
- Motivating Others
- Programming and Scripting Languages
- Statistics
- Technical Writing
More jobs at Candidate Experience site
All 49- Office Of The Customer QA AnalystCandidate Experience site · Johnston, RI, United States3d ago
- Director Front Office Models, Capital Markets & AdvisoryCandidate Experience site · Boston, MA, United States · USD 200,000–300,000/yr4d ago
- Private Bank, Deposit/Liquidity Product ManagerCandidate Experience site · United States · USD 128,000–150,000/yr4d ago
- Principal AI Security EngineerCandidate Experience site · United States · USD 150,000–190,000/yr6d ago
- Senior Solution Engineer - Agile PlatformsCandidate Experience site · United States · USD 114,000–120,000/yr6d ago
Similar roles
- Data EngineerNR Consulting - India · Chennai, TNjust now
- Marketing Data AnalystPyramid Consulting · Plano, TXtoday
- AWS Data EngineerQuadrant · Fairfax, VAtoday
- AI/ML DeveloperKasmo · Auburn Hills, MItoday
- Senior Analytics EngineerRedwood Materials · San Francisco, California, United Statestoday
- Senior Data Engineering ManagerRedwood Materials · McCarran, NVtoday