Staff Data Scientist
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Key skills for this role
About the Role
Clio seeks a Staff Data Scientist to lead forecasting architecture, develop high-impact ML models, and drive GenAI innovation. You will define technical standards, mentor junior scientists, and partner with engineering and product teams.
Key Skills for This Role
Responsibilities
- Define the long term forecasting roadmap and establish architectural standards for the entire company
- Lead the architectural design of complex ML systems, ensuring they are scalable, maintainable, and integrated seamlessly with the broader engineering stack
- Architect reusable, 'platform level' forecasting frameworks to be used by other Data Science teams
- Own the development of 'tier 1' models using advanced statistical, deep learning, or Reinforcement Learning techniques
- Tackle high ambiguity challenges, such as integrating causal inference or deep learning into global forecasts
- Act as the subject matter expert for Generative AI; design RAG architectures, evaluate foundation models, and establish fine tuning protocols
- Define the team’s technical standards for CI/CD, model versioning, and automated testing
- Audit codebases to ensure high performance and 'production ready' quality
- Own the end to end design and evaluation of high impact product and business experiments
- Provide deep technical guidance to more junior Data Scientists
- Influence the roadmap by identifying 'blind spots' in current data strategy and proposing novel solutions
- Partner with Data Engineering to optimize data pipelines for ML and with Product to ensure technical feasibility of the long term vision
Requirements
- 8+ years of experience in Data Science, Machine Learning, or a highly quantitative field, with a track record of deploying models that drove significant revenue or cost savings
- Mastery of System Design and state of the art time series research
- Proven ability to influence executive leadership and mentor senior technical staff
- Expertise in Python and SQL
- Advanced experience with AWS and Databricks
- Proficiency in distributed computing (e.g., Spark, Ray) and modern data platforms (Snowflake/Databricks)
- Hands on experience with LLM orchestration (LangChain, Haystack), vector databases, and PyTorch or TensorFlow
- Strong understanding of software engineering principles (microservices, API design) as they relate to deploying ML at scale
- Master’s or PhD in Computer Science, Physics, Statistics, Mathematics, or a related quantitative field
Full Job Posting
Summary
- Clio is the global leader in legal AI technology, empowering legal professionals and law firms of every size to work smarter, faster, and more securely.
- We are transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice.
Job Duties
- Define the long term forecasting roadmap and establish architectural standards for the entire company.
- Lead the architectural design of complex ML systems, ensuring they are scalable, maintainable, and integrated seamlessly with the broader engineering stack.
- Architect reusable, 'platform level' forecasting frameworks to be used by other Data Science teams.
- Own the development of 'tier 1' models—those with the highest business risk or technical complexity—using advanced statistical, deep learning, or Reinforcement Learning techniques.
- Tackle high ambiguity challenges, such as integrating causal inference or deep learning into global forecasts.
- Act as the subject matter expert for Generative AI; design RAG architectures, evaluate foundation models, and establish fine tuning protocols for proprietary data.
- Define the team’s technical standards for CI/CD, model versioning, and automated testing.
- Audit codebases to ensure high performance and 'production ready' quality.
- Own the end to end design and evaluation of high impact product and business experiments, establishing rigorous statistical standards and frameworks.
- Provide deep technical guidance to more junior Data Scientists.
- Influence the roadmap by identifying 'blind spots' in current data strategy and proposing novel solutions.
- Partner with Data Engineering to optimize data pipelines for ML and with Product to ensure technical feasibility of the long term vision.
Skills & Qualifications
- 8+ years of experience in Data Science, Machine Learning, or a highly quantitative field, with a track record of deploying models that drove significant revenue or cost savings.
- Mastery of System Design and state of the art time series research.
- Leadership without Authority: Proven ability to influence executive leadership and mentor senior technical staff.
- Deep Technical Stack: Expertise in Python and SQL; Advanced experience with AWS and Databricks; Proficiency in distributed computing (e.g., Spark, Ray) and modern data platforms (Snowflake/Databricks).
- Modern AI Toolkit: Hands on experience with LLM orchestration (LangChain, Haystack), vector databases, and PyTorch or TensorFlow.
- System Design: Strong understanding of software engineering principles (microservices, API design) as they relate to deploying ML at scale.
- Education: Master’s or PhD in Computer Science, Physics, Statistics, Mathematics, or a related quantitative field.
- Communication: Ability to persuade executive leadership on technical investments and 'sell' a long term technical vision.
What you will find here
- Competitive, equitable salary with top tier health benefits, dental, and vision insurance
- Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin and Sydney) to be in office min. twice per week.
- Flexible time off policy, with an encouraged 20 days off per year.
- CAD 2000 annual counseling benefit
- RRSP matching and RESP contribution
- Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years
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