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Senior Data Scientist – AI/ML & Generative AI
Actively Reviewing
Zensar Technologies
Job Description
Job Description
We are seeking a Senior Data Scientist to lead AI-driven initiatives delivering machine learning and Generative AI solutions within Capital Markets. This role focuses on building scalable models and applications for forecasting, anomaly/fraud detection, and LLM-based solutions (including RAG and agentic AI) on modern cloud platforms.
Key Responsibilities
Key Skills
Experience & Education
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
We are seeking a Senior Data Scientist to lead AI-driven initiatives delivering machine learning and Generative AI solutions within Capital Markets. This role focuses on building scalable models and applications for forecasting, anomaly/fraud detection, and LLM-based solutions (including RAG and agentic AI) on modern cloud platforms.
Key Responsibilities
- Design, develop, and deploy machine learning models for forecasting, classification, and anomaly/fraud detection
- Architect and implement Generative AI solutions, including RAG pipelines, prompt engineering, embeddings, and vector databases
- Build scalable AI applications leveraging LLM APIs, orchestration frameworks, and agent-based systems
- Develop modular, production-ready Python applications following robust software engineering practices (SOLID principles)
- Deploy, monitor, and optimise models using MLOps practices on platforms such as Azure, AWS, and Databricks
- Analyse large, complex datasets to derive actionable business insights
- Collaborate with cross-functional teams and effectively communicate outcomes to technical and business stakeholders
- Strong expertise in machine learning, statistical modelling, and data science techniques
- Hands-on experience with Generative AI, including LLMs, RAG, prompt engineering, and vector databases
- Practical experience with AI/LLM frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar
- Solid understanding of anomaly detection techniques (e.g. Autoencoders, XGBoost, Isolation Forest)
- Proficiency in Python and SQL, with ability to develop complex, modular, and maintainable applications
- Strong understanding of software engineering principles, including SOLID design principles
- Experience with Databricks and cloud platforms (Azure Preferred)
- Good understanding of Capital Markets domain and fraud detection use cases
- 6+ years of experience in Data Science, Machine Learning, or AI-related roles
- Bachelor’s degree required.
- Strong analytical thinking and problem-solving skills
- Clear and effective communication with both technical and non-technical stakeholders
- Delivery-focused with a pragmatic, cost-conscious mindset
- Ability to work independently and collaboratively in cross-functional teams
Key Skills
- Strong expertise in machine learning, statistical modelling, and data science techniques
- Hands-on experience with Generative AI, including LLMs, RAG, prompt engineering, and vector databases
- Practical experience with AI/LLM frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar
- Solid understanding of anomaly detection techniques (e.g. Autoencoders, XGBoost, Isolation Forest)
- Proficiency in Python and SQL, with ability to develop complex, modular, and maintainable applications
- Strong understanding of software engineering principles, including SOLID design principles
- Experience with Databricks and cloud platforms (Azure Preferred)
- Good understanding of Capital Markets domain and fraud detection use cases
Experience & Education
- 6+ years of experience in Data Science, Machine Learning, or AI-related roles
- Bachelor’s degree required.
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
Required Skills
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