Senior Data Scientist

Master’s or Ph.D. in Data Science, Computer Science, Statistics, Economics, or a related field.
3+ years of experience in data science, analytics, or a similar role.
Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) or R for modeling and analysis.
Solid experience with SQL for querying and managing structured data.
Knowledge of machine learning, statistical modeling, and optimization techniques.
Experience working with cloud platforms (AWS, GCP, Azure) and big data technologies.
Ability to communicate complex findings to non-technical stakeholders in a clear, concise manner.
Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn).

Develop, test, and implement predictive models and machine learning algorithms to solve business challenges.
Analyze large datasets to identify trends, patterns, and insights that inform strategic decisions.
Write efficient, scalable code for data analysis, model development, and automation using Python, R, SQL, or similar tools.
Design and execute experiments (A/B testing, causal inference, etc.) to measure the impact of business initiatives.
Collaborate with stakeholders to translate business questions into data science problems and communicate findings effectively.
Build and maintain data pipelines and ETL processes to ensure data quality and availability.
Present data-driven recommendations to executives and cross-functional teams in a clear and actionable manner.
Stay updated on the latest advancements in data science, machine learning, and AI.

Experience in causal inference, econometrics, or Bayesian methods.
Hands-on experience with ML Ops, model deployment, or data engineering workflows.
Understanding of business metrics, growth strategies, and financial modeling.
Ability to work in a fast-paced, cross-functional environment.