As a Data Science Consultant specializing in Generative AI, you will be responsible for designing, developing, and deploying AI-driven applications. You will work closely with cross-functional teams to analyze large datasets, build predictive models, and implement innovative AI solutions. This role requires a deep understanding of data science methodologies, proficiency in programming languages such as Python, and experience with modern AI/ML tools and cloud platforms.
Roles & Responsibilities
Requirement Gathering & Strategy
- Collaborate with stakeholders to understand business needs and translate them into analytical frameworks.
- Define the problem statement, determine key objectives, and develop data-driven strategies to achieve business goals.
- Work with cross-functional teams to align AI-driven solutions with the company’s broader strategy.
Data Processing & Analysis
- Identify, collect, and preprocess structured and unstructured data from various sources.
- Implement ETL processes to clean, transform, and manage data effectively.
- Handle missing values, outliers, and ensure data quality and consistency.
Model Development & Implementation
- Design and develop AI/ML models, particularly in the domain of Generative AI and Natural Language Processing (NLP).
- Implement solutions using Generative AI methodologies such as Prompt Engineering, Retrieval-Augmented Generation (RAG), Knowledge Graph-based RAG, and Fine-Tuning techniques like LoRA/QLoRA.
- Develop and deploy scalable AI/ML models using cloud-based services such as AWS, Azure, or Google Cloud Platform (GCP).
- Utilize multi-agent frameworks for RAG, rerankers for improved performance, and evaluation frameworks such as G-Eval.
Model Deployment & Governance
- Deploy AI solutions into production, ensuring efficiency, scalability, and performance optimization.
- Implement robust input and response governance mechanisms to ensure AI solutions meet ethical and compliance standards.
- Monitor model performance, retrain when necessary, and continuously improve AI solutions.
- Develop documentation, best practices, and training material for AI implementations.
Innovation & Research
- Stay up to date with the latest advancements in Generative AI, NLP, and deep learning.
- Experiment with cutting-edge AI/ML techniques and incorporate them into business solutions.
- Develop novel applications of AI in domains such as retail analytics, customer service automation, and enterprise knowledge management.
Core Skills & Experience
Minimum Qualifications
- Bachelor’s degree in Computer Science, Statistics, Economics, Business Economics, Econometrics, Operations Research, or a related field.
- 6-8 years of experience in Data Science and Analytics.
- Strong programming skills in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, and Scikit-Learn.
- Hands-on experience with Generative AI techniques and frameworks.
- Familiarity with ETL processes, data imputation, and outlier handling.
- Experience working with cloud AI/ML services on AWS, Azure, or GCP.
- Solid knowledge of SQL and database management.
Desirable Technical Skills
Sample Projects You Will Work On
- GenAI-powered Self-Serve Analytics. Building an AI-driven analytics tool for a global tech giant that leverages multi-agent frameworks and Azure OpenAI services to provide real-time insights from web analytics data.
- GenAI Document Query Bot. Creating an AI chatbot that allows users to interact with textual documents (e.g., FAQs, research reports) and receive personalized responses with citation-based validation.
- AI for KPI Analysis. Developing a GenAI-based bot for analyzing tabular datasets and responding to queries in textual, tabular, and visual formats for a leading global event agency.
- Advanced Information Retrieval with GenAI. Implementing AI-powered search and summarization solutions for structured data in a global technology enterprise.
- Time Series Forecasting with TimesFM. Building advanced forecasting models for a global retail chain using state-of-the-art AI techniques.
- GenAI-powered Shopping Assistant. Developing an AI shopping assistant for big-box retail stores, offering personalized recommendations.
- AI-driven Knowledge Retrieval for Enterprises. Using knowledge graphs and semantic search to enhance information accessibility and decision-making.
- Input and Response Governance in GenAI. Implementing best practices for responsible AI deployment and response validation.
- Training Foundational Models. Working on open-source large language models (LLMs) and small language models (SLMs) to adapt them to domain-specific data.
Why Join Infogain?
Infogain is a Silicon Valley-based digital platform and software engineering company that specializes in AI-driven business transformation. We partner with Fortune 500 companies and digital-first enterprises across technology, healthcare, insurance, travel, telecom, and retail industries. As a Microsoft Gold Partner and an Azure Expert Managed Services Provider, Infogain is at the forefront of AI, automation, cloud computing, and digital transformation.
- Work on high-impact AI solutions for global enterprises.
- Collaborate with some of the brightest minds in AI and data science.
- Gain exposure to the latest Generative AI techniques and cutting-edge technologies.
- Advance your career in a company that prioritizes employee growth and professional development.
Application Process
If you are a Data Science professional looking to take the next step in your career, apply now and be part of a team that is shaping the future of AI-driven analytics!