Principal Data Scientist

About CLARA

CLARA Analytics is the leading AI as a service (AIaaS) provider that improves casualty claims outcomes for commercial insurance carriers and self-insured organizations. The company’s product suite for workers comp, commercial auto and general liability insurance claims applies image recognition, natural language processing, and other AI-based techniques to unlock insights from medical notes, bills and other documents surrounding a claim. CLARA’s customers include companies from the top 25 global insurance carriers to large third-party administrators and self-insured organizations. Founded in 2017, CLARA Analytics is headquartered in California’s Silicon Valley. For more information, visit www.claraanalytics.com, and follow the company on LinkedIn and X.

About the Role

We are seeking an innovative and highly skilled Data Scientist with a passion for pioneering research and a proven ability to transition breakthrough ideas from the lab to production. This role is designed for a visionary thinker who combines deep data science expertise with advanced machine learning engineering (MLE) skills. If you excel at both designing cutting-edge NLP systems and implementing scalable, production-ready solutions, we want you on our team.

What You’ll Do...

• Innovative Research & Concept Development
  • Explore and experiment with new algorithms and methodologies to push the boundaries of current AI and NLP capabilities.
  • Author technical briefs that contribute to our thought leadership and drive strategic decision-making.
• Advanced NLP & ML System Design
  • Develop and refine NLP models to extract, classify, and summarize information from unstructured texts (e.g., claims documents, policies, and customer interactions).
  • Evaluate and benchmark cutting-edge deep learning architectures (including LSTM, RNN, CNN, BERT, and large language models) to ensure we’re always ahead of industry trends.
• From Idea to Production
  • Lead end-to-end machine learning projects, overseeing the full lifecycle—from early-stage research to robust deployment and continuous monitoring.
  • Implement best practices in ML engineering, ensuring that models are scalable, reproducible, and maintainable in production environments.
• Cross-Functional Collaboration
  • Work closely with actuaries, product managers, and data engineers to align AI strategies with business objectives.
  • Participate in code reviews, model reviews, and design discussions to ensure quality, transparency, and adherence to industry standards.
• Communication & Leadership
  • Translate complex quantitative concepts into clear, actionable insights for both technical and non-technical stakeholders.
  • Act as an evangelist for data-driven innovation, mentoring peers and helping build an environment of continuous learning and improvement.
• Ethics & Compliance
  • Ensure that all AI solutions adhere to ethical guidelines as well as data privacy and industry regulations (e.g., GDPR, HIPAA).
  • Incorporate explainable AI (XAI) techniques to maintain transparency and trust in model outcomes.

What We’re Looking For...

Required

• Educational Background: MS or higher in a quantitative discipline (e.g., Artificial Intelligence, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering).
• Experience:
  • Minimum 5 years in developing machine learning models with a strong emphasis on transitioning research into production.
  • At least 3 years of hands-on experience in natural language processing (NLP), coupled with a robust academic foundation.
• Technical Expertise:
  • Proficient in Python and experienced with libraries/frameworks including PySpark, TensorFlow, PyTorch, and MLFlow.
  • Adept with NLP frameworks and packages, including SpaCy and NLTK.
  • Solid understanding of various deep learning architectures, large language models, and emerging NLP technologies (e.g., LangChain, AWS Foundation Models).
• Communication: Proven ability to distill complex quantitative concepts into actionable insights for diverse audiences, driving stakeholder engagement through data-driven narratives.

Preferred

• Advanced Degree: PhD in a quantitative discipline.
• Specialized Skills:
  • Demonstrated experience in implementing explainable AI (XAI) strategies.
  • Familiarity with graph-based models and reinforcement learning.
• Domain Knowledge:
  • Experience in or exposure to insurance-specific processes (claims handling, risk modeling, actuarial science) is a plus.
  • Understanding of regulatory requirements and data privacy standards relevant to the industry.
• Industry Impact:
  • A track record of publication or participation in high-profile AI/ML competitions is highly desirable.

What We Offer...

• The opportunity to make a real impact on a growing company.
• Work on challenging and rewarding projects that will push your technical skills.
• Collaborative and supportive work environment.
• Competitive salary and benefits package.
  • Salary Range: $190 - 210k
  • Benefits: employer-provided health insurance and ancillary benefits (life, disability, etc.), flexible PTO, fully WFH, 401k with match
• Be a part of a team that is passionate about what we do.