Senior Data Scientist - Artificial Intelligence/Machine Learning (4-6 yrs)

Job Summary :

We are seeking a highly skilled Senior Data Scientist to lead and drive end-to-end AutoML/AI/ML solutions.

The ideal candidate will have extensive experience in machine learning, NLP, and recommender systems, with strong expertise in deploying scalable AI/ML solutions in a production environment.

Preference will be given to candidates from top-tier institutions (IIT, NITS, IIITS, BITS, RGUKTS) with a background in computer science or mathematics.

This role requires a blend of technical expertise, business acumen, and collaboration with cross-functional teams to deliver high-impact data science solutions.

Key Responsibilities :

- Lead and participate in the full lifecycle of AutoML/AI/ML solutions, including feasibility analysis, design, development, validation, and deployment.

- Ensure the seamless deployment of machine learning models into production through software development best practices.

- Collaborate with data architects and engineers to implement scalable AI/ML products.

- Write production-ready code and deploy real-time ML models while exposing ML outputs through APIs.

- Design and execute experiments to optimize models and drive business value.

Required Qualifications & Experience :

- 4+ years of relevant experience in applied machine learning, with at least two of the following areas: supervised/unsupervised learning, natural language processing (NLP), recommender systems.

- Graduate/Postgraduate degree in Mathematics, Computer Science, Statistics, Operations Research, or a related field.

- Strong expertise in classical machine learning algorithms, including:

- Regression, Tree-based models (Decision Trees, Random Forest, Gradient Boosting, XGBoost, LGBM), Support Vector Machines, Neural Networks, Stacking & Ensemble Techniques.

- Hypothesis Testing (T-test, Chi-Square, ANOVA), K-means Clustering, Time Series Forecasting, Collaborative Filtering.

Nice to have :

- Experience in Reinforcement Learning, Deep Learning (CNNs, RNNs, LSTMs).

- Hands-on experience with AutoML implementation at scale.

- Expertise in model building, validation, and production deployment, with a track record of taking models live in a production environment.

- Strong proficiency in Python and SQL.

- Experience with Cloud Technologies & Services such as Azure, Databricks, MLflow, ADF.

- Ability to communicate complex technical concepts to non-technical stakeholders.

- Familiarity with ML lifecycle management and MLOps tools & frameworks.

Preferred Skills & Attributes :

- Strong analytical and problem-solving skills.

- Ability to work in a fast-paced, agile environment.

- Passion for data science and continuous learning