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.
Our client invites you to join our dynamic and pioneering team, where your expertise in data science will significantly influence our path forward. They are passionate about tackling real-world challenges and seek like-minded individuals eager to make a mark in the retail pricing arena. Embark on this exciting journey with us and play a key role in sculpting the future of dynamic pricing in retail.
Required skills:
To excel in this role, candidates should possess the following qualifications and experiences:
- A Master’s or higher in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
- 3+ years of applied experience in, and a proven track record of using data to drive business results.
- Strong skills in python development, including package management, deployment, and unit testing.
- Proficiency in SQL and experience with large-scale data systems such as Hadoop or Spark.
- Deep understanding of data engineering principles, including ETL pipelines, data quality control and data scalability.
- Practical experience with AWS cloud services.
Nice-to-Haves:
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- Familiarity with MLOps infrastructure: CI/CD, software, data & model versioning control, observability, and deployment.
- Experience in AI/ML system design and implementation.
- Strong working knowledge and expertise in machine learning, statistical modeling, and data mining is a significant advantage.
- Hands-on familiarity with key python packages (e.g. polars/pandas, statsmodels, scikit-learn, pytorch, xgboost, etc.).
- Practical understanding of containerization with Docker and orchestration with Kubernetes.
,[We’re looking for ambitious individuals passionate about making a significant impact in the retail tech space. If you’re motivated by innovation and eager to contribute to a pioneering company shaping the future of retail pricing, They offers the perfect opportunity to challenge yourself and grow with us. Join us in our mission to transform pricing strategies into proactive, visionary actions that redefine retail success., Design and implement end-to-end solutions, covering system architecture and software development, to support our AI-driven services., Build scalable systems with integrated observability, logging, and tracing to quickly detect, understand, and resolve runtime issues., Collaborate with diverse teams, both internal and external to the R&D group, to drive product innovation and client success.] Requirements: Python, Data engineering, AI, Hadoop, ML, Quality control, AWS Cloud, MLOps, CI, CD, Machine learning, Data mining, pandas, scikit-learn, PyTorch, Docker
scikit-learn CI/CD pandas Analytical skills Python Amazon Web Services (AWS) Apache Spark Computer Science Data Engineering Applied Mathematics physics MLOps Docker SQL data-mining xgboost Kubernetes Machine Learning statsmodels ETL Hadoop PyTorch