Data Scientist - 2 | Location: Bangalore

 

At CommerceIQ, we help consumer brands accelerate their retail e-commerce market share growth and profitability through machine learning and algorithms. We are building the world’s most complete and sophisticated retail e-commerce management platform, which connects and intelligently automates the management of retail e-commerce channels like Amazon, Walmart, and Instacart across the entire e-commerce operational chain of retail media management, sales operations, supply chain, and digital self-analytics.

We are in hypergrowth mode, having raised our Series D funding at unicorn valuation (>$1B). Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail e-commerce platforms, and delivering exceptional customer service to unlock high net retention rates.

We are looking for a Data Scientist 2 to join our Bangalore team and work on problems in areas like product matching, product tagging, etc. 

Roles and responsibilities:

Understand the business problem and provide data science solutions.  Carry out proof of concept for data science problems. Collaborate with product and engineering teams to build data science solutions ( end to end )  Do exploratory data analysis to support existing and future data science projects. Build dashboards to monitor the data science project's performance and communicate the metrics to the business team.

Preferred Qualifications:

Work Experience : 3+  Years of data science experience Machine Learning Knowledge: Well versed with machine learning concepts and have built ML projects end to end. Understanding of mathematical concepts behind ML models. Statistical Data Analysis: Proficiency in applying statistical techniques to analyze data and generate useful business insights.  Data Visualization: Skill in creating meaningful visualizations of complex data sets using tools like Tableau, PowerBI, or Python libraries (e.g., Matplotlib, Seaborn). Model Evaluation and Tuning: Knowledge of techniques for evaluating and improving the performance of machine learning models. Coding Skills: Strong coding skills in Python. Able to write modular and reusable code.  Good to have experience of using LLMs for data science solutions