Data Scientist

Job Description

Position Summary

We are seeking a highly quantitative Data Scientist with a Ph.D. in Mathematics, Statistics, or a related quantitative field to develop advanced algorithms and analytical models that power product innovation and data-driven marketing strategies. This role sits at the intersection of data science, product development, and marketing, working closely with cross-functional teams to transform complex data into actionable intelligence and scalable solutions.

The ideal candidate is a strong researcher with a practical engineering mindset—comfortable developing novel models, testing hypotheses, and deploying solutions that drive measurable business impact. Key

Responsibilities

Algorithm & Model Development

Develop, test, and optimize machine learning models, predictive algorithms, and statistical frameworks for product and marketing applications.

Conduct advanced data analysis using techniques such as Bayesian modeling, time series forecasting, causal inference, reinforcement learning, anomaly detection, or optimization algorithms.

Build scalable solutions and partner with engineering teams to deploy models into production.

Cross-Functional Collaboration

Work with product teams to inform feature development, personalization strategies, experimentation design, and product roadmaps.

Collaborate with marketing to build customer segmentation models, attribution models, LTV forecasting, targeting strategies, and campaign optimization tools.

Translate scientific findings into clear business recommendations and partner with stakeholders to ensure adoption.

Data Exploration & Insights

Lead complex research initiatives—hypothesis formulation, experiment design, statistical validation, and result interpretation.

Analyze large datasets to uncover patterns, generate insights, and identify opportunities for product or marketing optimization.

Develop dashboards, metrics, and automated analytical systems to monitor model performance and business outcomes.

Experimentation

Design and evaluate A/B tests, multi-arm bandit experiments, and other controlled experiments to measure product and marketing impact.

Apply rigorous statistical methodologies to assess causal relationships and ensure scientific validity.

Documentation & Communication

Document model assumptions, methodologies, and results in a way that is clear, reproducible, and auditable.

Present findings and recommendations to leadership and cross-functional teams in a compelling and accessible manner.

Qualifications

Required

Ph.D. in Mathematics, Statistics, Applied Mathematics, Computer Science, or a related highly quantitative field.

Strong foundation in mathematical modeling, probability, statistical inference, and advanced analytics.

Proficiency in Python (Pandas, NumPy, SciPy, scikit-learn, PyTorch/TensorFlow preferred).

Experience building and deploying machine learning models end-to-end.

Experience working with large, complex datasets using SQL or similar tools.

Ability to communicate complex technical concepts to non-technical stakeholders.

Proven ability to work in cross-functional environments and manage multiple research streams.

Preferred

Experience in product analytics, digital marketing analytics, or algorithm development for consumer-facing applications.

Experience with cloud environments (AWS, GCP, or Azure).

Experience developing models for personalization, recommendation systems, LTV prediction, NLP, or optimization.

Experience with experiment design (A/B testing) and causal inference.

Experience with data visualization tools (e.g., Tableau, Looker) or programmatic visualization (matplotlib, seaborn, Plotly).

Key Competencies

Strong mathematical and statistical intuition

Research-driven, experimental mindset

Ability to translate complex quantitative work into business value

Curiosity, creativity, and scientific rigor

Strong communication and storytelling skills

Ability to work independently and as part of a cross-functional team

Why Join Us

Work on high-impact algorithms that directly shape product and marketing strategy

Collaborate with multidisciplinary teams and influence core business decisions

Opportunity to bring cutting-edge research into real-world applications

Supportive environment for ongoing learning, experimentation, and innovation