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# Data Scientist / Data Analyst (Product & Customer Analytics, Experimentation, GenAI) - W2 92/hr

- **Company:** Projas Technologies, LLC
- **Location:** Oakland, CA, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Big Data, Computer Programming, Data Mining, Data Visualization, R (Programming Language), Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Multivariate Testing, Power BI, Standard Sql, SQL Databases, Tableau (Software), Usage Analysis, Sql Optimization, Information Technology, Data Analytics, Looker Analytics
- **Published:** October 22, 2026
- **Apply:** https://www.dice.com/job-detail/f999c6ba-3638-45ac-98b3-215428d93976

## About the Role

* 4-6 years of experience in Data Science, Analytics, Product Analytics, Growth Analytics, or Business Intelligence.
 * Strong SQL programming and data analysis skills.
 * Experience with A/B Testing, Experiment Design, and Statistical Analysis.
 * Knowledge of Causal Inference methodologies such as Propensity Score Matching (PSM), Difference-in-Differences (DiD), or related approaches.
 * Experience working with BI and data visualization tools.
 * Strong communication and stakeholder management skills.
 * Ability to translate business requirements into analytical solutions.
 * Experience supporting product, marketing, or customer analytics initiatives.
 * Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Operations Research, Econometrics, or related quantitative field.

<>Required Skills

 * SQL
 * Data Modeling
 * Business Intelligence (BI)
 * Experimentation
 * A/B Testing
 * Statistical Analysis
 * Causal Inference
 * Customer Analytics
 * Product Analytics
 * Data Visualization
 * KPI Reporting
 * Stakeholder Communication
 * Banking Analytics
 * FinTech Analytics

<>Nice to Have

 * Experience in Banking, Lending, Payments, Financial Services, or FinTech.
 * Exposure to Machine Learning and AI-driven analytics.
 * Familiarity with predictive modeling and customer behavior analysis.
 * Experience supporting growth, retention, and marketing analytics use cases.

## Description

We are seeking a Data Scientist with strong analytics, experimentation, and business intelligence expertise to help drive data-driven decision making across customer onboarding, engagement, and retention initiatives. This role will partner closely with Product, Engineering, Marketing, and Design teams to generate actionable insights, execute experiments, and support AI-driven analytics initiatives within a fast-paced fintech environment.
<>Key Responsibilities

 * Analyze customer behavior across acquisition, onboarding, engagement, retention, and lifecycle journeys.
 * Develop data-driven recommendations that support business strategy and product growth initiatives.
 * Partner with Product Managers, Engineers, Marketing, and Design teams to solve business problems using analytics.
 * Design, execute, and evaluate A/B tests and experimentation frameworks.
 * Apply statistical analysis and causal inference methodologies to measure business impact.
 * Build dashboards, KPI reporting, and business intelligence solutions.
 * Support AI and machine learning initiatives by evaluating model outputs and translating results into meaningful business metrics.
 * Utilize SQL and data modeling techniques to transform and analyze large datasets.
 * Present findings and recommendations to stakeholders through clear visualizations and reports.
 * Collaborate with senior data scientists and contribute to analytical best practices., Data Scientist, Senior Data Scientist, Product Data Scientist, Analytics Scientist, Decision Scientist, Quantitative Analyst, Product Analyst, Business Intelligence Analyst, BI Analyst, Customer Analytics, Marketing Analytics, Growth Analytics, FinTech, Banking Analytics, Payments, Lending, Financial Services, SQL, Advanced SQL, Data Modeling, Data Analysis, Data Mining, Data Visualization, Tableau, Power BI, Looker, Business Intelligence, Experimentation, A/B Testing, Multivariate Testing, Statistical Analysis, Hypothesis Testing, Causal Inference, Propensity Score Matching, PSM, Difference in Differences, DiD, Machine Learning, AI Analytics, Predictive Analytics, Customer Segmentation, Retention Analytics, Product Analytics, KPI Reporting, Metrics Development, Stakeholder Management, Data Science, Python, R, Analytics Engineering, Decision Making, Customer Behavior Analysis.