About The Chance
• FlashAid is an AI-driven health insurance technology company transforming how businesses discover, purchase, and manage insurance. We build scalable solutions using data, machine learning, and automation to simplify insurance distribution, customer acquisition, and servicing.
• This role is for a hands-on Data Science Engineer who can write production-quality code, develop machine learning models, and deploy AI-powered solutions — combining software engineering, data science, and applied ML with ownership from concept to production. Role & Responsibilities
• Build, train, evaluate, and deploy predictive models for lead scoring, customer segmentation, conversion propensity, and sales forecasting.
• Develop recommendation engines and analyze historical insurance, renewal, and claims datasets to generate actionable insights.
• Explore NLP, LLM, and generative AI approaches where they solve practical business problems.
• Write clean, scalable Python code and expose models through APIs integrated with business applications.
• Build reliable data pipelines and implement testing, monitoring, versioning, and retraining for deployed models.
• Improve inference performance, operational reliability, and code quality.
• Prepare structured and unstructured datasets through validation, transformation, and feature engineering.
• Partner with product, sales, and business teams to turn use cases into measurable AI solutions.
• Follow strong data privacy, security,



and responsible model-development practices. Skills & Qualifications Must-Have
• Proficiency in Python and SQL; experience with Pandas, NumPy, and statistical modeling.
• Experience with ML libraries such as scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• API/backend development using FastAPI, Flask, or similar frameworks.
• Experience with relational or NoSQL databases, Git, Docker, and cloud platforms (AWS/Azure/GCP).
• Working knowledge of model deployment, monitoring, and MLOps.
• B.
E./B.
Tech./M.
Tech./M.
Sc. in Computer Science, Data Science, AI/ML, or a related discipline.
• 2–5 years of relevant hands-on experience building ML or AI applications.
• Evidence of at least one end-to-end model developed and deployed into a usable application.
• Strong problem-solving ability and independence to own implementation. Preferred
• Exposure to LLM APIs, RAG, or AI agents.
• Startup, fintech, or insurtech experience. Benefits & Culture Highlights
• Work on real-world insurance data and build intelligent sales and recommendation products.
• Own meaningful AI projects end-to-end in a fast-moving product environment.
• Collaborate closely with founders, technology, and business leadership.

Skills:
pytorch,mlops,ai agents,lightgbm,azure,tensorflow,xgboost,python,git,flask,llm,docker,numpy,rag,scikit-learn,sql,aws,fastapi,pandas,google cloud platform

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