Senior Data Scientist - AI/ML

Location: Bangalore

Work Mode: Hybrid

Experience: 5+ Years

We are looking for a Senior Data Scientist with a strong foundation in Machine Learning, Algorithms, Statistical Modeling, and AI-native development to contribute to advanced AI initiatives and real-time analytics platforms.

This is a hands-on, technically deep role for professionals passionate about building scalable and intelligent ML solutions.

Key Responsibilities

• Design, build, and optimize ML models for real-world, large-scale datasets.

• Develop solutions for predictive modeling, anomaly detection, forecasting, and automated alerting.

• Apply classical ML techniques including regression, classification, clustering, and ensemble methods.

• Work with deep learning architectures such as CNNs, RNNs/LSTMs, Transformers, and attention mechanisms.

• Analyze time-series and complex real-time data.

• Develop POCs and take ML solutions from experimentation to production.

• Process and analyze large-scale datasets using Ray and Spark.

• Collaborate with engineering and product teams to integrate ML models into production systems.

• Contribute to AI roadmaps and AI-driven product initiatives.

• Leverage AI coding tools such as Claude, Cursor, or GitHub Copilot for development, debugging, prototyping, and solution design.

Required Skills

• 5+ years of experience in Data Science / Applied Machine Learning.

• Advanced proficiency in Python; Scala or similar languages is a plus.

• Strong knowledge of:

• Machine Learning & Statistical Modeling

• Regression, Classification & Ensemble Methods

• Clustering & Dimensionality Reduction

• Neural Networks & Deep Learning

• CNNs, RNNs/LSTMs, Transformers & Attention

• Optimization, Bayesian & Probabilistic Modeling

• Strong ability to take models from POC to scalable production solutions.

• Hands-on experience with AI-assisted development tools.

• Strong analytical, problem-solving, and communication skills.

Good to Have

• Experience with real-time data processing and streaming analytics.

• Strong knowledge of time-series analysis, forecasting, seasonality, and change-point detection.

• Experience building AI-powered alerting or anomaly detection systems.

• Knowledge of MLOps and cloud-based ML deployment.

• Experience with model monitoring, versioning, retraining pipelines, or production ML systems.

• Experience integrating or fine-tuning LLMs/foundation models.