Responsibilities

- Analyze large, complex datasets to uncover trends, patterns, anomalies, and actionable business insights.
- Design, develop, and deploy AI and GenAI applications that address business needs using machine learning, large language models, and intelligent workflow orchestration.
- Build and optimize predictive, statistical, and time series models for business and operational use cases.
- Develop robust data pipelines, ETL workflows, and feature engineering processes using SQL and Python to support AI/ML applications.
- Lead Python-based application development for automation, data transformation, model integration, API development, and AI-powered workflows.
- Develop LLM-powered solutions such as copilots, knowledge assistants, summarization tools, search-and-retrieval solutions, and domain-specific recommendation systems.
- Apply Generative AI techniques including prompt engineering, retrieval-augmented generation (RAG), orchestration frameworks, grounding strategies, response evaluation, and workflow integration.
- Prototype and productionize AI application architectures, including integrations with vector databases, model APIs, cloud services, and enterprise systems.
- Contribute to the evaluation, monitoring, and continuous improvement of AI systems, including model quality, hallucination reduction, latency, cost, and user experience.
- Collaborate with product managers, engineers, analysts, domain experts, and business stakeholders to define, prioritize, and deliver AI-driven solutions.
- Translate business problems into scalable AI/ML and GenAI use cases, technical designs, and implementation roadmaps.
- Develop and enhance dashboards, reports, and BI solutions using Tableau where needed to support model insights and business decisions.
- Ensure strong data quality,



governance, security, compliance, and responsible AI practices across solution development and deployment.

Technical Skills/ Qualifications:

- Bachelor’s degree in Computer Science, Data Science, Engineering, AI, or a related field; master’s degree or advanced certification preferred.
- 5–7 years of experience in data science, advanced analytics, AI engineering, or related roles.
- Strong proficiency in Python for data science, API integration, automation, and AI application development.
- Advanced proficiency in SQL, including complex querying, performance tuning, data transformation, and data modeling.
- Strong knowledge of statistics, machine learning algorithms, applied mathematics, and time series analysis.
- Hands-on experience with Generative AI and large language model applications, including prompt engineering, RAG patterns, model evaluation, and practical enterprise use case implementation.
- Experience building AI applications using frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, and exposure to modern GenAI frameworks such as LangChain, LlamaIndex, or similar tools.
- Experience integrating with foundation model APIs and deploying AI solutions in production environments.
- Familiarity with vector databases, embeddings, semantic search, document retrieval, and knowledge-grounded AI applications.




- Understanding of MLOps / LLMOps, CI/CD pipelines, model versioning, testing, and release management.
- Exposure to cloud platforms such as AWS, Azure, or GCP, including AI/ML services and scalable deployment patterns.
- Experience with Git and version control best practices.
- Experience with Dataiku is an advantage.
- Expertise in Tableau or similar BI tools for reporting and stakeholder communication is desirable.
- Desirable domain awareness of industrial systems such as compressors, motors, power systems, refrigeration systems, and IC engines.
- Solid understanding of responsible AI, data governance, security, and compliance considerations in AI solution development.

Soft Skills:

- Strong analytical and problem-solving skills with a structured, methodical approach.
- Excellent verbal and written communication skills with the ability to explain complex topics clearly.
- Ability to work effectively with both technical and non-technical stakeholders.
- Strong collaborative and team-oriented mindset with a proactive, customer-focused, and results-driven approach.
- Ability to work independently with minimal supervision and manage multiple priorities.
- High ownership, attention to detail, and commitment to timely, accurate delivery.
- Adaptability to changing priorities, technologies, and business needs

We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.

📌 Senior Data Scientist (Bengaluru)
🏢 Sourceo
📍 Bengaluru