Python
Data Science
Machine Learning (ML)Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.
Location – Pune
Job Responsibilities
- Work closely with data scientists and data analysts to build models and continuous data monitoring workflows.
- Implement algorithms / models within companies recommendation engine framework.
- Own the MLOps life-cycle; build and own ML model life-cycle management process encompassing coding to building robust model monitoring workflows.
- Consult with product and business teams to build prototypes and then deploy holistic machine learning solutions.
- Recommend and implement architecture to deploy machine learning pipelines and CI/CD processes at scale
Skills Needed
- Minimum 3 years of experience as Machine Learning Engineer
- Knowledge of machine learning and statistics
- Strong experience working in the areas of time series analysis, reinforcement learning, NLP, optimization and heuristics based implementation to solve real-world problems
- Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind
- Strong knowledge of coding in Python and libraries such as Pandas, Numpy, Scikit-Learn, PyTorch, etc.
- Experience handling Big Data leveraging technologies like Snowflake, Spark. Ability to work in a big data ecosystem - expert in SQL and ability to work in distributed databases.
- Able to refactor data science code and has collaborated with data scientists in developing ML solutions.
- Experience playing the role of full-stack data scientist and taking solutions to production.
- Educational qualifications should be preferably in Computer Science, Statistics, Engineering or a related area.
Subodh Popalwar
Software Engineer, Memorres
About Graasai
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Follow CutshortSubodh Popalwar
Software Engineer, Memorres