Data Scientist

About the Project:

Our partner is revolutionizing retail with their dynamic pricing B2B SaaS platform, leading the charge in automating and optimizing pricing strategies with AI-driven insights. Their comprehensive solution, embraced by retailers and brands across over 40 markets, delivers actionable pricing recommendations that drive business growth and profitability. Since 2018, they've been empowering a wide range of industries, including consumer electronics, beauty, and apparel, to seamlessly integrate pricing strategies across online and offline channels.

Required skills:

- A Master’s or PhD in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.

4+ years of professional experience in:

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- End-to-end machine learning lifecycle (design, development, deployment, and monitoring).

- Advanced Python development, including OOP, writing production-grade code, testing, and optimization.

- Data mining, statistical analysis, and effective data visualization techniques.

- Deep familiarity with modern ML/DL methods and frameworks (e.g., PyTorch, XGBoost, scikit-learn, statsmodels).

- Strong analytical skills combined with practical experience interpreting model outputs to drive business decisions.

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Nice-to-Haves:

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- Practical knowledge of SQL and experience with large-scale data systems like Hadoop or Spark.

- Familiarity with MLOps tools and practices (CI/CD, model monitoring, data version control).

- Experience in reinforcement learning and Monte-Carlo methods.

- A solid grasp of microeconomic principles, including supply and demand dynamics, price elasticity, as well as econometrics.

- Experience with cloud services and platforms, preferably AWS.

Scope of work:

As a Data Scientist, you’ll play a critical role in shaping and enhancing our AI-driven pricing platform.

Specifically, you will:

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- Develop and Optimize Advanced ML Models: Build, improve, and deploy machine learning and statistical models for forecasting demand, analyzing price elasticities, and recommending optimal pricing strategies.

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- Lead End-to-End Data Science Projects: Own your projects fully, from conceptualization and experimentation through production deployment, monitoring, and iterative improvement.

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- Innovate with Generative and Predictive AI Solutions: Leverage state-of-the-art generative and predictive modeling techniques to automate complex pricing scenarios and adapt to rapidly changing market dynamics.