Senior Data Scientist

Kroll; San Francisco (CA); On-site; USD 60,000 - 150,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) with match

Generous PTO

Job summary

Kroll is seeking an experienced Senior Data Scientist to lead end-to-end ML initiatives within the Enterprise Data Group. You will mentor junior team members and partner with business and engineering stakeholders to translate complex problems into production-grade data science solutions.

The role spans fintech product development, digital transformation, process automation with ML, BI, data governance, and generative AI.

Qualifications

• Advanced degree required in a quantitative field (MS/PhD).
• 5+ years of applied ML experience with production delivery.
• Strong Python and modern ML stack experience.

Responsibilities

• Design, research, implement, and evaluate ML solutions across ML, DL, NLP, and GenAI.
• Build and fine-tune models from traditional to transformer-based architectures.
• Develop prompts, evaluation frameworks, and guardrails for LLM applications.

Skills

Python

Scikit-learn

PyTorch

TensorFlow

Pandas

Hugging Face

Databricks

Spark/PySpark

Azure

LLM/GenAI

Prompt engineering

Education

MS or PhD in CS/Statistics

Tools

MLflow

Unity Catalog

Azure OpenAI

Job description

Kroll is hiring a Senior Data Scientist to join its Enterprise Data Group. This role is designed for an experienced practitioner who can lead end-to-end ML initiatives, mentor junior team members, and partner with business and engineering stakeholders to translate complex problems into production-grade data science solutions.

Our program spans fintech product development, digital transformation, process automation with machine learning, business intelligence, data governance, and generative AI. You will work alongside an advanced data science and engineering team — and collaborate with professionals from the world's largest financial institutions, law enforcement agencies, and government bodies.

Day-to-Day Responsibilities:

• Design, research, implement, and evaluate machine learning solutions spanning traditional ML, deep learning, NLP, and LLM/GenAI applications
• Build and fine-tune models — from gradient-boosted trees and classical statistical models to transformer-based architectures and retrieval-augmented generation (RAG) systems
• Develop and optimize prompts, evaluation frameworks, and guardrails for LLM-powered applications
• Engineer scalable data and ML pipelines in Databricks using PySpark, Delta Lake, and MLflow
• Deploy, monitor, and maintain models in production on Azure (Azure AI Foundry, Azure OpenAI, Azure Functions, AKS), including CI/CD, model versioning, and drift detection
• Validate model inputs, outputs, and business impact; establish robust testing and monitoring practices
• Partner with engineering, product, and business stakeholders to scope problems and translate ML capabilities into measurable outcomes
• Communicate technical concepts, tradeoffs, and results to non-technical audiences, including senior leadership and clients
• Mentor junior data scientists and contribute to team standards around code quality, experimentation, and responsible AI
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, analytics, or a related quantitative field
• 5+ years of applied machine learning experience, including delivering models to production
• Strong Python skills and experience with the modern ML stack (scikit-learn, PyTorch or TensorFlow, pandas, Hugging Face Transformers)
• Hands-on experience with Databricks (notebooks, jobs, MLflow, Unity Catalog) and Spark/PySpark
• Production experience on Azure — ideally including Azure AI Foundry, Azure OpenAI Service, and Azure Data Lake
• Breadth across ML domains: traditional/statistical ML, deep learning, NLP, and LLM/GenAI applications, including hands-on experience with prompt engineering, RAG, embeddings, and agentic workflows
• Practical experience building LLM/GenAI applications — prompt engineering, RAG, fine-tuning, embeddings, vector databases, and evaluation
• Solid grounding in the full ML lifecycle: data validation, feature engineering, model design, experimentation, deployment, and monitoring
• Experience with structured and unstructured data, including text, documents, and semi-structured sources
• Strong statistical foundation and ability to reason about uncertainty, bias, and model risk
• Excellent technical and business communication skills

Preferred Traits:

• Experience in financial services, risk, compliance, or regulatory domains
• Familiarity with MLOps tooling (MLflow, Docker, Kubernetes, Azure DevOps or GitHub Actions)
• Hands-on experience with agentic AI frameworks (LangChain, LlamaIndex, Semantic Kernel), LLM evaluation tooling, and production deployment of GenAI applications

Knowledge of responsible AI practices, including fairness, explainability, and data privacy

Healthcare Coverage: Comprehensive medical, dental, and vision plans.

Time Off and Leave Policies: Generous paid time off (PTO), paid company holidays, generous parental and family leave.

Protective Insurances: Life insurance, short- and long-term disability coverage, and accident protection.

Compensation and Rewards: Competitive salary structures, performance-based incentives, and merit-based compensation reviews.

Retirement Plans: 401(k) plans with company matching.

About Kroll

Join the global leader in risk and financial advisory solutions—Kroll. With a nearly century-long legacy, we blend trusted expertise with cutting-edge technology to navigate and redefine industry complexities. As a part of One Team, One Kroll, you’ll contribute to a collaborative and empowering environment, propelling your career to new heights. Ready to build, protect, restore and maximize our clients’ value? Your journey begins with Kroll.

We are proud to be an equal opportunity employer and will consider all qualified applicants regardless of gender, gender identity, race, religion, color, nationality, ethnic origin, sexual orientation, marital status, veteran status, age or disability.

The salary range for this role is $60,000 - $150,000 USD