Data Scientist

Job Description:

Key Responsibilities:

1. Model Development:

- Design, develop, and implement end-to-end predictive models (forecasting, churn, propensity, lifetime value) and prescriptive models (optimization, recommendation engines) to drive product decisions.

2. Business Impact:

- Partner with product and business stakeholders to deeply understand their challenges, translating vague business goals into concrete mathematical, machine learning, or statistical frameworks.

3. Data Engineering & Pipeline Support:

- Clean, preprocess, and engineer complex features from structured and unstructured data sources, ensuring data integrity throughout the modeling lifecycle.

4. Deployment & Scaling:

- Collaborate with machine learning engineers (MLEs) to transition successful prototype models into robust, scalable production environments.

5. Experimentation & Evaluation:

- Design robust A/B testing, multivariate testing, and statistical validation strategies to measure the real-world impact and accuracy of deployed models.

6. Data Storytelling:

- Translate highly technical machine learning concepts, assumptions, and metrics into actionable business stories and visualizations for leadership.

Key Skills:

Core Technical Skills:

- Programming: Mastery of Python or R (with extensive use of libraries like Pandas, NumPy, Scikit-Learn).

- Database Management: Advanced SQL for extracting and manipulating data across relational and non-relational distributed databases.

- Machine Learning Frameworks: In-depth knowledge of regression, classification, clustering, time-series forecasting, and optimization algorithms.

- Statistical Analysis: Strong fundamentals in probability, hypothesis testing, and statistical significance.

Preferred Skills (Highly Desirable):

- Familiarity with cloud platforms (AWS, GCP, or Azure) for model deployment.

- Experience with big data frameworks (such as Apache Spark or Databricks).

- Knowledge of deep learning frameworks (TensorFlow or PyTorch).

- Experience with BI/Visualization tools (Tableau, PowerBI) to showcase prescriptive analytics.