About the role
Kroll is hiring a Senior Data Scientist for its Enterprise Data Group.
This program involves building fintech products, driving digital transformation of Kroll services, process automation with machine learning, business intelligence, data governance, and the development of generative AI solutions. You will work alongside an advanced engineering and data science team and collaborate with professionals from the world's largest financial institutions, law enforcement agencies, and government bodies.
This is a senior-level position for an experienced practitioner who can lead end-to-end ML initiatives, mentor junior team members, and partner with stakeholders to translate complex business problems into production-grade data science solutions.
At Kroll, your work will help deliver clarity to our clients' most complex governance, risk, and transparency challenges. Apply now to join One team, One Kroll.
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 ML, 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
REQUIREMENTS:
- 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 Machine Learning, Azure OpenAI Service, and Azure Data Lake
- Demonstrated experience across multiple ML domains: traditional/statistical ML, deep learning, and NLP
- 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:
- Experience in financial services, risk, compliance, or regulatory domains
- Familiarity with MLOps tooling (MLflow, Docker, Kubernetes, Azure DevOps or GitHub Actions)
- Experience with agentic AI frameworks (LangChain, LlamaIndex, Semantic Kernel) and LLM evaluation tools
- Knowledge of responsible AI practices, including fairness, explainability, and data privacy
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.
In order to be considered for a position, you must formally apply via careers.kroll.com.
Kroll is committed to equal opportunity and diversity, and recruits people based on merit.
The current salary range for this position is $100,000 to $150,000
#DNI
Not the right fit? Search for Data Scientist jobs in Toronto, ON
About Kroll Inc.
As the leading independent provider of risk and financial advisory solutions, Kroll leverages our unique insights, data and technology to help clients stay ahead of complex demands. Kroll's team of more than 6,500 professionals worldwide continues the firm’s nearly 100-year history of trusted expertise spanning risk, governance, transactions and valuation. Our advanced solutions and intelligence provide clients the foresight they need to create an enduring competitive advantage. At Kroll, our values define who we are and how we partner with clients and communities. Learn more at Kroll.com.
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About the role
Kroll is hiring a Senior Data Scientist for its Enterprise Data Group.
This program involves building fintech products, driving digital transformation of Kroll services, process automation with machine learning, business intelligence, data governance, and the development of generative AI solutions. You will work alongside an advanced engineering and data science team and collaborate with professionals from the world's largest financial institutions, law enforcement agencies, and government bodies.
This is a senior-level position for an experienced practitioner who can lead end-to-end ML initiatives, mentor junior team members, and partner with stakeholders to translate complex business problems into production-grade data science solutions.
At Kroll, your work will help deliver clarity to our clients' most complex governance, risk, and transparency challenges. Apply now to join One team, One Kroll.
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 ML, 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
REQUIREMENTS:
- 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 Machine Learning, Azure OpenAI Service, and Azure Data Lake
- Demonstrated experience across multiple ML domains: traditional/statistical ML, deep learning, and NLP
- 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:
- Experience in financial services, risk, compliance, or regulatory domains
- Familiarity with MLOps tooling (MLflow, Docker, Kubernetes, Azure DevOps or GitHub Actions)
- Experience with agentic AI frameworks (LangChain, LlamaIndex, Semantic Kernel) and LLM evaluation tools
- Knowledge of responsible AI practices, including fairness, explainability, and data privacy
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.
In order to be considered for a position, you must formally apply via careers.kroll.com.
Kroll is committed to equal opportunity and diversity, and recruits people based on merit.
The current salary range for this position is $100,000 to $150,000
#DNI
Not the right fit? Search for Data Scientist jobs in Toronto, ON
About Kroll Inc.
As the leading independent provider of risk and financial advisory solutions, Kroll leverages our unique insights, data and technology to help clients stay ahead of complex demands. Kroll's team of more than 6,500 professionals worldwide continues the firm’s nearly 100-year history of trusted expertise spanning risk, governance, transactions and valuation. Our advanced solutions and intelligence provide clients the foresight they need to create an enduring competitive advantage. At Kroll, our values define who we are and how we partner with clients and communities. Learn more at Kroll.com.