Role
As a Data Scientist, you will contribute to developing and deploying innovative AI andmachine learning solutions that transform insurance operations through intelligentautomation. You'll work on sophisticated models for Fraud, Waste & Abuse (FWA)detection, Intelligent Document Processing (IDP), and Agentic AI systems that powerautonomous insurance workflows including underwriting, claims processing, and policyservicing.This role offers excellent opportunities for growth and learning - you'll contribute to coreproduct development, support customer implementations, and assist with proof-of-conceptdevelopment under the guidance of senior team members. Working with our advanced techstack including LLM fine-tuning, computer vision, and multi-agent systems, you'll solvecomplex problems that directly impact how insurance companies operate and serve theircustomers.As we scale from successful startup to enterprise-level positioning, you'll develop yourexpertise in production machine learning, learn best practices from experienced practitioners,and contribute meaningfully to AI solutions that maintain the highest standards of accuracy,reliability, and business impact. If you're passionate about applying data science to real-worldinsurance challenges and want to grow your career while seeing your models transformbusiness processes, this role offers excellent opportunities for professional development.Model Development & Implementation
- Develop and implement machine learning models for fraud detection, risk
assessment, and anomaly detection using established algorithms and frameworks
under senior guidance
- Build computer vision and NLP models for intelligent document processing,
including document classification, OCR optimization, and automated information
extraction
- Implement and fine-tune Large Language Models (LLMs) for insurance-specific
applications, applying techniques such as LoRA, QLoRA, and PEFT to create
domain-specialized solutions
- Develop predictive models for underwriting, claims processing, and medical risk
assessment that support enhanced decision-making and operational efficiency
- Perform feature engineering and exploratory data analysis to identify patterns and
insights that inform model development and business understanding
AI Agent Development & Support
- Contribute to the development of autonomous AI agents for handling insurance
workflows with appropriate supervision and guidance
- Implement agent components and workflows that support multi-agent coordination
and decision-making processes
- Build conversational AI capabilities that can interact with users and systems to
gather information and provide recommendations
- Support the development of intelligent decision-making systems that adapt to
varying business requirements and regulatory constraints
- Assist with the implementation of agent monitoring, evaluation, and improvement
processes
Data Processing & Analysis
- Build and maintain data pipelines for model training, validation, and inference using
modern data engineering tools and practices
- Implement data quality checks and validation processes that ensure model inputs
meet accuracy and consistency requirements
- Perform comprehensive data analysis to understand data characteristics, identify
quality issues, and inform model development decisions
- Create data visualizations and analytical reports that communicate insights to
technical and business stakeholders
- Work with diverse data sources including structured insurance data, unstructured
documents, and external data feeds
Model Deployment & Monitoring Support
- Support model deployment processes from development through production,
working with MLOps teams to ensure smooth transitions
- Implement model monitoring and performance tracking capabilities that detect
issues and support continuous improvement
- Contribute to A/B testing and model evaluation frameworks that enable data-driven
decisions about model performance
- Develop model documentation and explainability features that support business
understanding and regulatory compliance
- Participate in model maintenance and improvement activities based on production
performance and business feedback
Collaboration & Learning
- Work closely with senior data scientists, solution architects, and software engineers
to deliver high-quality technical solutions
- Support customer-facing activities by adapting models for specific client needs and
contributing to implementation success
- Contribute to proof-of-concept development and technical demonstrations that
Showcase Our Capabilities To Prospective Customers
- Participate in code reviews, technical discussions, and knowledge sharing activities
that support team learning and best practices
- Stay current with emerging trends and techniques in AI/ML, particularly in areas
relevant to insurance and autonomous agents
Qualifications & Experience
Academic Qualifications
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics,
Mathematics, Engineering, or related quantitative field from a recognized institution
- Coursework or training in machine learning, statistics, or data analysis preferred
Professional Experience
- 3+ years of hands-on experience in data science, machine learning, or related
analytical roles with demonstrated ability to develop and deploy ML models
- Experience with machine learning project lifecycle from data exploration through
model deployment
- Background in applying statistical methods and machine learning algorithms to solve
business problems
- Exposure to production ML systems, model deployment, or MLOps practices
Preferred
- Insurance industry exposure preferred, with understanding of claims processing,
underwriting, medical risk assessment, or fraud detection workflows
Technical Skills
- Strong proficiency in Python with experience using Scikit-Learn, Pandas, NumPy,
and Jupyter for data science workflows
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or
similar libraries for model development
- Basic to intermediate knowledge of LLM fine-tuning, natural language processing,
or computer vision techniques. Understanding of embeddings, TF-IDF, and linguistic
modelling.
- Familiarity with OCR technologies, document processing, or computer vision
libraries such as OpenCV
- Experience with GenAI frameworks including LangChain, Hugging Face
Transformers, or vector databases
- Knowledge of data manipulation and analysis using SQL, big data tools, or
distributed computing frameworks
- Understanding of MLOps concepts, version control systems, and basic cloud
platform usage
Communication & Collaboration Skills
- Strong analytical and problem-solving skills with ability to approach complex
business problems systematically
- Good communication abilities for presenting technical findings to team members
and stakeholders
- Collaborative mindset with willingness to learn from senior team members and
contribute to team success
- Attention to detail and commitment to producing high-quality, reliable analytical
work
- Enthusiasm for learning new technologies and staying current with developments in
AI/ML and insurance technology
How We Get Things DoneAt our core, we believe in building intelligent systems that transform how insurance works.We're a team of innovators who combine deep technical expertise with real-world businessimpact. Our guiding principles center around technical excellence, data-driven decisionmaking, and the responsible development of AI systems that enhance human capabilities.We foster a culture of continuous learning, experimentation, and cross-functionalcollaboration. As we scale from startup to enterprise, we maintain our commitment tocutting-edge research while building solutions that can handle the most demanding insurance workflows globally.Championing Inclusion & InnovationWe embrace the opportunity to build a team that reflects diverse perspectives andexperiences. Being an equal opportunity employer means we consider qualified candidatesbased on merit, technical capabilities, and cultural fit, regardless of background, identity, orpersonal characteristics.We're committed to creating an inclusive environment where innovative thinking thrives andwhere every team member can contribute to our mission of transforming insurance throughintelligent automation.Skills: ml,processing,python,sql,pandas,pytorch,insurance,numpy,ocr technologies,data,machine learning,data science,learning,genai frameworks,scikit-learn,tensorflow,computer vision,data analysis,natural language processing,mlops,jupyter
