Data Scientist 1
At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.
We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.
Data Scientist - 1 | Location: Bangalore
Roles and responsibilities :
- Understand the business problem and provide data science solutions.
- Building data science solutions end to end.
- 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 projects performance and communicate the metrics to the business team.
Preferred Qualifications :
- Work Experience : 0-2 Years of data science experience
- Machine Learning Knowledge : Well versed with Machine Learning concepts and have built ML projects end to en. 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.