Mahindra & Mahindra—Data Scientist

Job description

Description: Experience Level: 2-5 years Location: Bengaluru Education: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or related fields. A strong academic pedigree is highly preferred. Overview: We are seeking a talented and motivated Data Scientist to join our team. The ideal candidate will have 2-5 years of hands-on experience in the development and deployment of Machine Learning (ML) projects. Exposure to Computer Vision and Natural Language Processing (NLP), especially Large Language Models (LLMs), will be a significant advantage. Key Responsibilities: - Develop, deploy, and optimize ML models for prediction and forecasting tasks on tabular/text datasets. - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. - Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) to support model development. - Build and deploy end-to-end ML pipelines, including model training, evaluation, and serving in production environments. - Monitor and maintain deployed models to ensure robustness, scalability, and performance over time. - Implement feedback loop into prediction. - Drive innovation: Explore, experiment with, and integrate cutting-edge ML techniques and frameworks into projects. - Document workflows, methodologies, and findings for both technical and non-technical stakeholders. Key Skills and Qualifications: Core Expertise: - Proficiency in Python and popular ML libraries such as Scikit-learn, TensorFlow, or PyTorch. - Strong understanding of supervised and unsupervised ML algorithms. - Hands-on experience with model deployment tools such as Docker, Flask, FastAPI, or cloud-based ML services (AWS SageMaker, GCP Vertex AI, etc.). - Proficiency in working with structured/unstructured data, SQL. Added Advantage: - Experience in Computer Vision (e.g., OpenCV, YOLO, or related frameworks). - Exposure to NLP/LLMs (e.g., Hugging Face, GPT, or BERT). - Familiarity with MLOps practices, CI/CD pipelines for ML, and model monitoring (MLFlow). General Skills: - Strong problem-solving skills and attention to detail. - Excellent communication skills to convey technical concepts to diverse audiences. - Ability to work in a fast-paced environment and manage multiple priorities effectively.