Data Scientist
Snaphunt
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
- 3 years 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
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