Location: Indiranagar, Bangalore
Experience: 5+ Years
Compensation: ₹30–40 LPA
Work Mode: On-site
About the Role
We are looking for a Senior Data Scientist with 5+ years of experience to lead the development of data-driven solutions and machine learning systems.The ideal candidate should have strong expertise in machine learning, statistical modeling, Python, and data analysis, with hands-on experience taking models from experimentation to production.
Key Responsibilities
- Design, develop, and deploy machine learning models for real-world business problems.
- Analyze large and complex datasets to identify trends, patterns, and actionable insights.
- Develop predictive models, classification, regression, recommendation, and forecasting solutions.
- Build and optimize end-to-end ML pipelines.
- Work closely with engineering, product, and business teams to translate business problems into data science solutions.
- Perform feature engineering, model selection, training, validation, and optimization.
- Evaluate model performance using appropriate statistical and ML metrics.
- Work with structured and unstructured data.
- Deploy and monitor machine learning models in production environments.
- Improve existing models and data pipelines for scalability, accuracy, and reliability.
- Mentor junior data scientists and contribute to data science best practices.
- Stay current with developments in AI, Machine Learning, Generative AI, and advanced analytics.
Required Skills
- 5+ years of experience in Data Science / Machine Learning.
- Strong programming skills in Python.
- Strong understanding of statistics, probability, and machine learning fundamentals.
- Hands-on experience with scikit-learn, Pandas, NumPy, and related ML libraries.
- Experience with supervised and unsupervised learning techniques.
- Strong SQL skills and experience working with large datasets.
- Experience with feature engineering and model evaluation.
- Strong understanding of data preprocessing and exploratory data analysis.
- Experience taking ML models from prototype to production.
- Strong analytical and problem-solving skills.
Good to Have
- Experience with Deep Learning using PyTorch or TensorFlow.
- Experience with NLP, Generative AI, LLMs, or recommendation systems.
- Knowledge of RAG, embeddings, vector databases, or AI agents.
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Familiarity with Docker, Kubernetes, MLflow, or similar MLOps tools.
- Experience with Spark or other distributed data-processing frameworks.
- Experience mentoring or leading other data scientists.
- What We’re Looking ForStrong technical and statistical foundation.
- Ability to solve ambiguous business problems using data.
- Strong ownership from problem definition → experimentation → model development → deployment → monitoring.
- Ability to communicate complex analytical findings clearly to technical and non-technical stakeholders.
- A practical, business-oriented approach to machine learning.
- Someone who enjoys building production-grade ML solutions, not just prototypes.