Senior Data Scientist

Senior Data Scientist (NLP)

About CLARA Analytics

Clara Analytics' mission is to give insurance claims managers the power to improve outcomes dramatically, save millions of dollars, and help thousands of people recover from injuries, recoup damages, and get back on their feet faster after suffering a loss.

The opportunities to develop high-value AI and machine learning applications in the insurance industry are nearly unbounded - the sector has only just begun to realize the benefits of adopting these technologies. We are looking for high performers with an entrepreneurial spirit who welcome the challenges and opportunities of thinking big in uncharted territory and are driven to solve challenging problems and develop cutting-edge applications that have a significant impact.

Job Description

We are seeking a highly motivated and skilled Senior Data Scientist to contribute to the design, development, and deployment of NLP-based systems and machine learning models for cost analysis and predictions. This role requires a deep understanding of data science techniques, strong programming skills, and experience with real-world applications of AI.

Responsibilities

• Data Analysis: Perform exploratory data analysis (EDA) as required when building new models or evaluating existing models.
• NLP Model Development: Build and optimize NLP models to extract, classify, and summarize information from unstructured text such as claims documents, policies, and customer interaction.
• Collaborative Problem-Solving: Partner with cross-functional teams, including actuaries, product managers, and software engineers, to align AI solutions with business goals.
• Code and Model Quality: Participate in code and model reviews to ensure high-quality, version-controlled artifacts and objects are available to support transparency, traceability, and explainability of all work
• Documentation and Reporting: Document methodologies, assumptions, and findings, and communicate results to technical and non-technical stakeholders effectively.
• Compliance and Ethics: Ensure all AI solutions adhere to ethical guidelines and comply with relevant data privacy and industry standards.
• Communication, Education and Evangelism: Translating data science principles & methods into business relevant messaging for leaders

Qualifications

• MS degree in a quantitative discipline (e.g., artificial intelligence, statistics, operations research, economics, computer science, mathematics, physics, electrical engineering).
• 5 years of experience developing machine learning models, including 2 years of model deployment experience.
• 3 years of practical experience in natural language processing, plus a strong academic background.
• Hands on experience with text preprocessing, named entity recognition, entity linking, and topic modeling.
• Experience with natural language processing techniques and algorithms including LSTM, RNN, CNN, and embeddings such asBERT.
• Ability to assess the pros and cons of different NLP methods and algorithms, break problems down into standard tasks and prototype quickly.
• Experience with large language models and their associated tools/platforms/frameworks (LangChain, ChatGPT, AWS Foundation Models, Llama2, etc.) for use in querying large documents and entity extraction.
• Proficient in Python, with experience in libraries like PySpark, Tensorflow, Pytorch, MLFlow, and NLP packages like SpaCy andNLTK.
• Demonstrated ability to communicate complex quantitative concepts effectively to audiences of varying technical proficiency.

Preferred Qualifications

• PhD in quantitative discipline as described above.
• Experience in implementing explainable AI (XAI) techniques.
• Knowledge of graph-based models or reinforcement learning.
• Familiarity with insurance-specific regulations and data privacy standards (e.g., GDPR, HIPAA).
• Understanding of insurance processes, including claims handling, risk modeling, or actuarial science.
• Publication or participation in AI/ML competitions is a plus.

What We Offer

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Opportunities for professional development, including conferences and training.
• A collaborative and inclusive work environment.