Senior Data Scientist

We are looking for a Senior Data Scientist to join our growing team. In this role, you will play a key part in developing and implementing advanced analytics, machine learning models, and optimization algorithms that enhance our core product offerings. You will work closely with cross-functional teams, including data engineers, software developers, and business stakeholders, to solve complex problems and drive data-driven decision-making.

Who you are:

• Develop and enhance ML models for demand forecasting, inventory optimization, and product similarity.
• Design and implement algorithms that improve retail and supply chain decision-making.
• Work with large-scale datasets to extract actionable insights and drive business value.
• Collaborate with data engineers to build scalable data pipelines and production-ready models.
• Communicate findings and recommendations to both technical and non-technical stakeholders.
• Stay up-to-date with the latest advancements in AI, machine learning, and optimization techniques to continuously improve our solutions.
  
  

• Master’s or Ph.D. in Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, or a related field.
• 5+ years of experience in data science, machine learning, or AI, preferably in a retail or supply chain domain.
• Strong proficiency in Python and experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Expertise in predictive modeling, time series forecasting, and optimization techniques.
• Experience working with SQL.
• Familiarity with cloud platforms (AWS, GCP, Azure) and deployment of machine learning models in production.
• Ability to translate business problems into data-driven solutions.
• Excellent problem-solving skills and strong analytical thinking.
• Strong communication and presentation skills.
  
  

• Experience in reinforcement learning.
• Background in retail analytics, supply chain optimization, or revenue management.
• Experience working with big data technologies and ETLs like Spark, S3, and Kafka