Algorithm Engineer

A successful InsurTech startup that has developed a data-driven operating system for the insurance industry. Their platform enables major insurance providers to optimize marketing and distribution processes by predicting the lifetime value of individual customers and ensuring optimal acquisition pricing.

Already integrated with some of the largest insurance companies in the US, the company is leveraging advanced analytics to drive higher profitability through precision marketing.

Located in the Central District, the company operates a hybrid model with one day of remote work per week.

Role Overview-

• Joining as the First and Sole Data Scientist in the organization, reporting initially within the Product unit.
• Building the company's AI and ML capabilities from the ground up, with full ownership of the technical roadmap in this domain.
• Developing sophisticated models for Predictive Modeling, Classification, Clustering, and Time Series Forecasting.
• Designing and deploying ML Pipelines into production environments to enable automated decision-making at a large scale.
• Working at the intersection of Data Science and Business Metrics to create algorithms that directly impact ROI and customer acquisition strategies.

Requirements-

• 5 years of professional experience as a Data Scientist or ML Engineer.
• Deep hands-on experience in building and scaling ML Pipelines within cloud environments.
• Proven expertise in Predictive Modeling, Time Series Forecasting, Clustering, and Classification.
• Strong proficiency in Python and SQL – Mandatory.
• Practical experience with Cloud platforms (AWS, GCP, or Azure) for the deployment of ML models in production.
• Extensive experience working with Large-scale Datasets, including deep understanding of Data Pipelines and Feature Engineering.
• Familiarity with Deep Learning, Reinforcement Learning, or Generative AI.
• Ability to work independently as a "Sole Function," translating business objectives into technical AI solutions.

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