Data Scientist (ML & Statistics)

Role Overview

We are seeking a Data Scientist who can turn statistical ideas into models that loyalty clients rely on every day. The role is roughly 70% technical (modeling, statistics, engineering of ML systems) and 30% business (framing problems, working with clients, translating results into decisions).

What You Will Do

Design, train and validate models for churn, propensity, next-best-offer, lifetime value, tier migration and anomaly or fraud detection. Experimentation & Causal Inference (technical): Design A/B tests and holdouts for campaigns, offers and program changes, including power analysis and sample sizing.

Why It Might Be a Fit

To be successful in this role, you should have: Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Engineering, Data Science or a related quantitative field. An MBA or a post-graduated degree in Analytics is an added advantage.

Requirements

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Engineering, Data Science or a related quantitative field.
• 1–4 years of experience building and deploying ML or statistical models in production, ideally in a SaaS, consumer or loyalty/CRM setting.
• Strong Python (pandas, NumPy, scikit-learn, XGBoost/LightGBM, statsmodels; PyTorch or TensorFlow is a plus) and strong SQL.
• Solid statistical foundations: hypothesis testing, regression, probability, Bayesian methods, time-series, survival analysis and experimental design.
• Experience with cloud data platforms such as Snowflake, BigQuery, Redshift, Databricks or Vertica, and with large-scale data processing (Spark is a plus).
• Working knowledge of a BI tool (Tableau, Power BI, Looker or similar) to share model outputs.
• Experience with causal inference or uplift modeling is preferred.
• Exposure to enterprise SaaS products or customer loyalty programs is preferred.
• Strong communication skills: able to explain model logic, trade-offs and uncertainty to non-technical stakeholders.
• Understanding of Agile methodologies and comfort working in a fast-paced environment.

Benefits

• Competitive salary
• Stock options
• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Flexible work arrangements
• Opportunities for professional growth and development