Job Title : GenAI & Data Science Lead

Location : Bangalore

Experience : 5 - 8 Years

Employment Type : Full-Time

Job Summary :

We are looking for a GenAI & Data Science Lead to design, build, and deploy enterprise-grade AI and Generative AI solutions. The ideal candidate will have strong hands-on experience across Generative AI, Machine Learning, Data Engineering, and BI, with the ability to translate complex business problems into scalable AI-driven solutions. This role requires technical leadership, strong analytical thinking, and close collaboration with cross-functional teams.

Key Responsibilities :

- Design, develop, and deploy Generative AI and Machine Learning models for use cases such as text generation, predictive analytics, NLP, and computer vision

- Lead data preprocessing, feature engineering, and exploratory data analysis (EDA)

- Build and deploy enterprise-grade AI solutions with a focus on scalability, accuracy, and performance

- Work closely with business, product, and engineering teams to integrate AI solutions into core workflows

- Develop and support data engineering pipelines and BI solutions

- Monitor model performance, drift, and reliability; continuously optimize deployed models

- Present insights, findings, and recommendations to stakeholders

- Stay current with emerging trends in Generative AI, MLOps, and data science

Mandatory Skills :

- Hands-on experience with Generative AI frameworks and models (GPT, BERT, DALL-E or similar)

- Strong programming skills in Python and PySpark

- Experience with ML libraries : TensorFlow, PyTorch, Scikit-learn

- Solid expertise in data analysis and visualization (Pandas, NumPy, Matplotlib / Seaborn / Plotly)

- Strong understanding of NLP, Computer Vision, and data modelling techniques

- Experience working with cloud platforms: AWS, Azure, or GCP

- Strong background in Data Engineering and BI

- Banking / BFSI domain experience is mandatory

- Exposure to product-based environments is an added advantage

Technical Skills :

- Programming : Python, SQL

- ML / AI Frameworks : TensorFlow, PyTorch, Scikit-learn

- Generative AI : GPT, BERT, DALL-E, LLM-based solutions

- Data Processing : Pandas, NumPy, Spark

- Visualization : Matplotlib, Seaborn, Plotly

- Cloud Platforms : AWS, Azure, GCP

- Version Control : Git

- Model Deployment : Docker, Kubernetes

- ETL & BI Tools : Any standard BI / ETL tools

- Data Platforms : Databricks, Snowflake

Good to Have :

- Experience with data pipeline and orchestration tools (Apache Airflow, Apache Kafka)

- Familiarity with MLOps practices and CI/CD for ML

- Knowledge of deep learning and reinforcement learning

- Experience in model explainability, interpretability, and fairness

- Certifications in Databricks, Dataiku, Snowflake, or related platforms

Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, AI, or related field

- 5- 8 years of experience in AI, Data Science, and Data Engineering

- Proven track record of deploying AI/ML models into production

Key Result Areas :

- Successful delivery and deployment of AI and Generative AI solutions

- High model accuracy, performance, and scalability

- Effective collaboration with cross-functional teams

- Continuous optimization and maintenance of deployed models

Key Performance Indicators :

- Model accuracy and performance metrics

- Deployment success rate and system uptime

- Reduction in manual effort through automation

- Stakeholder satisfaction and business impact

- Efficiency of data processing and model training