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: 
- 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.

‍

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