Data Scientist

Role Summary

The Lead Data Engineer will strategically work in the data science team in applying advanced analytics, machine learning, LLMs and cutting-edge technologies to propose, perform and evaluate exploratory data analysis and predictive modelling to address critical ecommerce challenges. A creative and flexible approach to problem-finding should be combined with a strategical approach to maintaining the highest standards of data-driven decision-making with faithful application of development best practices.

Duties & Responsibilities :

• Develop and deploy sophisticated machine learning and deep learning models to solve critical business challenges such as predict customer patterns, recommendation systems, demand forecasting, and predictive analytics.
  

• Leverage advanced techniques to extract insights, automate customer interactions, and enhance user experience across e-commerce platforms.
  

• Conduct thorough testing and validation of models, employing techniques such as cross-validation, A/B testing, and performance benchmarking to ensure models deliver accurate, reliable, and consistent results.
  

• Implement dynamic pricing strategies powered by reinforcement learning, Bayesian optimization, and price elasticity modeling, integrating real-time market intelligence and competitive data to optimize profitability and market share.
  

• Work closely with cross-functional teams to identify impactful business problems, and operationalize models using scalable deployment frameworks
  

• Stay informed of emerging trends and advancements in data science, machine learning operations, and AI ethics, continuously integrating new tools and techniques into the team's workflow.
  

• Ability to drive teams to success; ability to drive change and influence peers, leaders, collaborators, and individual contributors. Experience leading end-to-end data science project implementations working with Agile methodologies.
  

What you Bring to the Table:

• Design, develop and implement business and technical features.
  

• Work with Architects to ensure the system is implemented as designed and in adherence with development guidelines and security standards.
  

• Partner with business, Product teams and other domain architects to translate business requirements and vision into core eCommerce functions.
  

• Create and evolve application documentation as required.
  

• Ensure that technical solutions follow best practices, are reliable and are easily maintainable
  

Years of Experience :

Minimum of 6 years of experience with complex data science, applied statistics, machine learning, or mathematical modeling projects




Requirements

Basic Qualifications:

• Bachelor’s degree in in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field. Alternately equivalent experience in data analysis and predictive modeling will be considered in lieu of relevant degree.
  

• 6+ years of experience with complex data science, applied statistics, machine learning, or mathematical modeling projects.
  

• Hands on experience with deep learning frameworks, LLMs, GenAI tools, and applying NLP techniques.
  

• Expertise using tools like TensorFlow, PyTorch, LightGBM, XGBoost as well as general purpose programming languages such as GPT-4, BERT is preferred.
  

• Strong understanding of data and coding skills with SQL and Python.
  

• Excellent analytical abilities and a strong intellectual curiosity
  

• Experience with cloud platforms (e.g., Azure, AWS, GCP)
  

• Proficient understanding of code versioning tools, such as Git / SVN
  

Preferred Qualifications:

• Master’s degree in computer science, Engineering, or a related field.
  

• Experience working in retail domains and developing e-commerce solutions.
  

• Familiarity with Agile methodologies and ability to thrive in fast-paced, collaborative environments.