Data Scientist II, TDI

NPS Prism

Title:Data ScientistII, TDI (Work From Home)

Company Profile:

NPS Prismis a market-leading, cloud-based SaaS business owned by Bain & Company. NPS Prism provides its customers with actionable insights and analysis that guide the creation of game-changing customer experiences. Based on rock-solid sampling, research, and analyticmethodology, it lets customers see how they compare to their competitors on overall NPS, and on every step of the customer journey.

WithNPS Prismyou can see whereyourestrong, where you lag, and how customers feel about doing business with you and your competitors, in their own words. The result: Prioritize the customer interactions that matter most. NPS Prism customers use our customer experience benchmarks and insights to propel their growth and outpace the competition.

Launched in 2019,NPS Prismhas rapidly grown to a team of over 200, serving dozens of clients around the world. NPS Prism is 100% owned by Bain & Company, one of the top management consulting firms in the world and a companyconsistently recognizedas one of the worlds best places to work. We believe that diversity,inclusionand collaborationiskey to building extraordinary teams. We hire people with exceptional talents,abilitiesand potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally.

Position Summary:

NPS Prism has experienced tremendous growth as a standalone software and data business over the past few years and is making the leap from being a consulting-led business to a technology-led business. Given that shift, we are looking to build our team with world-class team members to help drive business growth to its full potential in this next phase. This isa great opportunityto help build the largest startup owned by Bain & Company and take NPS Prism into the future.

We are seeking aData Scientist IIwith experience in bothclassical machine learning(regression, classification, predictive modeling) andmodern AI systems(LLMs, Generative AIand agentic frameworks).

The role requires strong applied modeling skills across structured and unstructured data, and experience deploying models into production environments.

This position involves end-to-end ownership of data science initiatives, from problem framing and experimentation to deployment and monitoring.

Key Responsibilities:

• Develop and deployAIsolutions acrossMLand othergenAIuse cases.

• Design, build,validateandoptimizepredictive models includingregression,tree-based models,ensemble methods,gradientboostingand

  
  deep learningarchitectures whereappropriate.

• Develop and deployLLM-basedandGenerative AIsolutions, including retrieval-augmented generation (RAG),prompt engineering,fine-tuningandagentic workflows.

• Buildmulti-agent systemsand tool-integrated AI solutions for analytics automation, insight generation and conversational interfaces.

• Apply statistical analysis, hypothesistestingand experimental design (including A/B testing) to inform business decisions.

• Collaborate with cross-functional teams

• Ensure production readiness through monitoring, model governance, performance tracking, retrainingstrategiesand documentation.

• Analyze structured and unstructured datasets to generate actionable insights.

• Communicate analytical findings and technicalconcepts clearlyto cross-functional stakeholders.

• Contribute to code reviews, bestpracticesand continuous improvement ofAIinfrastructures.

• Independently manage projects in environments with evolving requirements and timelines.

Required Qualifications, Experience & Skills:

Qualifications:

Education:

• Bachelors orMasters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.

Experience:

• 2+ years of professional experience in data science or applied machine learning roles.

• Demonstrated experience delivering regression and/or classification models in production environments.

• Hands-on experience building and deploying LLM-based or Generative AI applications.

• Hands-on experience with agentic frameworks such asCrewAI,LangChainAgents,LangGraphorsimilar multi-agent orchestration frameworks.

Skills:

• Strongproficiencyin Python

• Solid foundation in statistics, regression,classificationandother classical MLtechniques.

• Hands-on experience with LLMs and Generative AI, including prompt engineering, RAG,fine-tuningand evaluation.

• Experience building multi-agent systems using frameworks such asCrewAI,LangChain/LangGraphor similar.

• Familiarity with vector databases and embedding pipelines.

• Experience deploying ML/LLM solutions in production withMLOpspractices (e.g.,MLflow, CI/CD) on cloud platforms (AWS/Azure/GCP/Databricks).

• Strong problem-solving and cross-functional communication skills.