Gen AI-Data Science Lead

Role & responsibilities

Job Summary

We are seeking a talented Gen AI & Data Science Engineer to join our dynamic team in Bangalore. The ideal candidate will have 5 to 8 years of hands-on experience in developing AI and data science models, with expertise in Generative AI, machine learning, and data engineering. You will be responsible for designing and implementing AI solutions to address complex business challenges and drive data-driven decision-making.

Mandatory Skills

• Proficiency in Generative AI frameworks (like GPT, BERT, DALL-E).
• Strong programming skills in Python and Pyspark.
• Experience with ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Proficiency in data analysis and visualization tools (Pandas, NumPy, Matplotlib).
• Strong understanding of NLP, computer vision, and data modelling techniques.
• Experience with cloud platforms (AWS, Azure, GCP).
• Experience in Data Engineering and BI
• Banking/BFSI Domain Experience.
• Any product experience is an added advantage.

Key Responsibilities

• Design and develop data science models for various applications, including text generation, image synthesis, and predictive analytics.
• Perform data preprocessing, data cleaning, and feature engineering.
• Build and deploy machine learning models using state-of-the-art techniques.
• Build and deploy enterprise grade AI solutions.
• Collaborate with cross-functional teams to integrate AI solutions into business processes.
• Conduct exploratory data analysis and present insights to stakeholders.
• Stay updated with advancements in generative AI and data science.
• Ensure model accuracy, performance, and scalability.

Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field is preferred.
• Proven experience as an AI & Data Science Engineer with 3 to 5 years of relevant experience. 5-8 years in the area of data (Data Engineering & BI) is preferred

Technical Skills

• Programming Languages: Python, SQL.
• Frameworks: TensorFlow, PyTorch, Scikit-learn.
• Generative AI Models: GPT, BERT, DALL-E.
• Data Processing Tools: Pandas, NumPy, Spark.
• Data Visualization: Matplotlib, Seaborn, Plotly.
• Cloud Platforms: AWS, Azure, GCP.
• Version Control: Git.
• Model Deployment: Docker, Kubernetes.
• Any ETL & BI Tools
• DW/Datalake Databricks, Snowflake

Soft Skills

• Strong problem-solving and analytical thinking.
• Excellent communication and collaboration skills.
• Adaptability to new technologies and tools.
• Creative and innovative mindset.

Good to Have

• Experience with data pipeline tools (Apache Airflow, Apache Kafka).
• Familiarity with MLOps practices.
• Knowledge of reinforcement learning and deep learning techniques.
• Experience with model interpretability and fairness.
• Certifications in Databricks, Dataiku, Snowflake

Work Experience

• Minimum of 5-8 years of experience as an AI & Data Science Engineer. With experience in data engineering and BI.
• Proven track record of developing and deploying AI models in production environments.

Compensation & Benefits

• Competitive salary and annual performance-based bonuses
• Comprehensive health and optional Parental insurance.
• Optional Retirement savings plans and tax savings plans.

Preferred candidate profile

Key Result Areas (KRAs)

• Successful development and deployment of AI models.
• High accuracy and efficiency of generative AI solutions.
• Effective collaboration with cross-functional teams to integrate AI into workflows.
• Maintenance and optimization of deployed models.

Key Performance Indicators (KPIs)

• Model accuracy and performance metrics.
• Deployment success rate and uptime.
• Reduction in manual effort through automation.
• Positive feedback from stakeholders.
• Efficiency in data processing and model training.