Principal Data Scientist

14 hours ago

Mumbai Maharashtra, India TVS Motor Full time

**Group Company**: TVS Motor Company

**Designation**: Principal Data Scientist (PDS_D&AI - Common Engineering, DPM - CE)

**Office Location**: Electronic City (Territory), Karnataka Koramangala (Territory)

**Position description**:
Need to deliver solutions to production through the software development lifecycle

Provide leadership to establish world-class ML lifecycle management processes.

Write production ready code and deploy real time ML models; expose ML outputs through APIs

Partner with data/ML engineers and vendor partners for input data pipes development and ML models automation

Good to have hands-on experience with open source tools such as Kaldi, Py torch-Kaldi.

**Primary Responsibilities**:

- Build ML/AI models leveraging a strong understanding of Machine Learning principles including standard algorithms for Regression and Classification, Deep Learning constructs
- Build recommender systems around agent Collections prioritization, product recommendations, and personalization engines.
- Build sophisticated pricing engines based on AI powered product evaluation tools.
- Build cross-sell/up-sell recommender systems using deep learning frameworks, and with sparse data.
- Able to understand the determinants of success for a Machine Learning system, Model accuracy and efficiency, Data requirements, Training and Test constructs, CI/CD for ML systems.
- Able to build standard ML systems using available ML components provided by AWS, Azure and GCP.
- Cloud & Big Data:

- 1. Work on Cloud Infrastructure (Azure, AWS) to provision data to ML models, build ML systems on deploy them at scale.
- 2. Build ML systems using Spark libraries such as ML Lib, Spark SQL and be able to deploy them on clusters/machines, both on Cloud and on-Prem.
- 3. Put in place systems to continuously monitor, evaluate and re-train ML models in production.
- 1. Design and implement the machine learning lifecycle at scale, from building the data infrastructure to train/test Machine learning models to their production environments.
- 2. Management of production ML workflows ensuring automated CI/CD capabilities are built into the workflow.
- 3. Design and Implement alerts/dashboards to ensure continuous monitoring of production models’ effectiveness (accuracy, latency, performance etc.,)

**Educational qualifications preferred.**
- **Category**: bachelor's degree, master's degree
- **Degree**: Master's Degree, Bachelor's degree

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