Every day, somewhere in the world, important decisions are made. Whether it is a private equity company deciding to invest millions into a business or a large corporation implementing a new strategic direction, these decisions impact employees, customers, and other stakeholders.
Consulting and private equity firms come to proSapient when they need to discover knowledge to help them make great decisions and succeed in their goals. It is our mission to support them in their discovery of knowledge.
We help our clients find industry experts who can provide their knowledge via interview or survey: we curate this knowledge in a market-leading software platform; and we help clients surface knowledge they already have through expansive knowledge management.
We’re on the hunt for a Senior Data Scientist to lead groundbreaking AI/ML initiatives that transform how we deliver expert recommendations, enhance information retrieval, and automate workflows. If you’re passionate about LLMs, NLP, and recommendation systems- and love seeing your work make a real commercial impact- this is the role for you!
This isn’t just about building models; it’s about solving real-world problems with AI. We need someone who thrives in a high-impact, hands-on environment, breaking down complex business challenges into well-defined data science solutions that drive tangible product and business improvements.

REQUIREMENTS

• Develop and deploy AI/ML solutions by translating business problems into data-driven projects. Leverage state-of-the-art AI/ML models, including OpenAI, Amazon Comprehend, and open-source alternatives, for applications such as content-based recommendations, entity extraction, and text processing.
• Design and run statistically sound experiments with datasets, working closely with the business operations team to collect relevant data and evaluating models with a focus on business impact and performance.
• Build scalable AI/ML infrastructure by collaborating with engineering teams to deploy and optimize ML models in production, ensuring efficient use of OpenSearch/Elasticsearch, and Kafka for real-time data processing and search.
• Drive continuous improvement and innovation by staying updated on advancements in LLMs, ML, and AI, identifying emerging techniques to enhance models, algorithms, and system performance.
• Communicate insights effectively by presenting model results and findings to both technical and non-technical stakeholders, ensuring alignment with business objectives.

REQUIRED QUALIFICATIONS

• Strong expertise in ML/NLP, including semantic search, summarization, personalization, classification, information retrieval, and recommendation systems, with a solid understanding of ML algorithms (e.g., clustering, decision trees, gradient descent).
• Experience with a modern ML-Ops workflows for developing and deploying models.
• Hands-on experience with LLMs, covering prompt engineering, fine-tuning, domain adaptation (Experience with RAG and AI agents is considered an advantage).
• Expertise in Python and any data processing frameworks and pipelines (e.g. pandas, kedro, kafka streams).
• Knowledge of backend development for deploying production-grade models.
• Ability to communicate complex technical concepts to both technical and business audiences.

Please refer the Job description for details