Job Title: Data Scientist
Overview
We are seeking a highly skilled Data Scientist to join our marketing analytics organization. In this role, you will leverage statistical modeling, machine learning, and data engineering techniques to deliver insights, build predictive models, and support data‑driven decision‑making across the business conducting ad-hoc analysis. The ideal candidate is analytically strong, curious, and comfortable working with large datasets and modern data technologies.
Key Responsibilities
Analytics & Modeling (40%)
- Build, validate, and deploy machine learning models (classification, regression, forecasting, clustering, NLP, etc.)
- Conduct statistical analyses and A/B tests to evaluate business performance and product changes.
- Translate ambiguous business questions into structured analytical problems.
Data Engineering & Preparation (10%)
- Acquire, clean, and manipulate large datasets from multiple sources.
- Build reproducible data pipelines using Python, SQL, and Snowflake.
- Work closely with data engineers to optimize data structures and improve data availability.
Insights & Business Impact (40%)
- Deliver clear, actionable insights to stakeholders through ah-hoc analysis, dashboards, visualizations, and written summaries.
- Partner with product, marketing, finance, and operations teams to identify opportunities for optimization.
- Support KPI development and help teams understand business trends.
Model Deployment & Monitoring (10%)
- Collaborate with engineering teams to deploy models into production environments.
- Monitor model performance and retrain/adjust, as necessary.
- Maintain documentation, reproducibility, and version control of all modeling work.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
- 3–7+ years of experience applying data science techniques in a business environment.
- Proficiency in Python (pandas, scikit‑learn, NumPy, statsmodels) or other model building tools.
- Strong SQL skills and experience with relational or cloud databases.
- Deep understanding of statistical modeling, hypothesis testing, and experiment design.
- Experience with machine learning, feature engineering, and model evaluation.
- Ability to communicate complex concepts to non‑technical audiences.
- Ability to perform ad-hoc analysis for LOBs.
Preferred Qualifications
- Experience with cloud platforms such as Snowflake, Azure, AWS, or GCP.
- Experience with big data tools (Spark, Databricks, Snowflake, BigQuery, Redshift).
- Experience with deep learning (PyTorch, TensorFlow) or NLP.
- Experience building dashboards in Power BI, Tableau, or similar tools.
- Experience as a data analyst conducting ad-hoc analysis.
- Knowledge of data governance and model lifecycle best practices.
Soft Skills
- Strong problem‑solving and critical‑thinking skills.
- Comfort working in fast‑paced, ambiguous environments.
- Curiosity and a continuous learning mindset.
