Data Scientist at Reliance HMO

We’re a health insurance company that acts like a technology company. We’re using software, data science and telemedicine to make health insurance more affordable, easier to access and more of a delightful experience
We are hiring a Senior Data Scientist to lead the transformation of complex datasets into actionable insights that drive strategic business outcomes. The role involves designing and deploying advanced machine learning models, performing statistical analysis, and creating clear, impactful data stories for both technical and non-technical stakeholders.
The ideal candidate is highly analytical, curious, and collaborative, with experience in end-to-end data science project delivery, including model deployment, experimentation, and evaluation.

As a Data Scientist, you will do the following:

Lead end-to-end data science projects, from data collection and preprocessing to model deployment and delivery.
Design, implement, and maintain advanced ML models, including regression, clustering, anomaly detection, and NLP applications.
Write optimized SQL queries to extract, manipulate, and analyze large datasets.
Translate complex data insights into actionable recommendations for technical and non-technical stakeholders.
Collaborate with cross-functional teams to define data requirements and implement scalable analytical solutions.
Monitor model performance, conduct A/B tests, and implement improvements to maintain accuracy and reliability.
Document methodologies, workflows, and data dictionaries to ensure reproducibility and knowledge sharing.
Mentor and guide junior data scientists, promoting best practices and technical excellence.

Requirements

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.
Minimum 4-5 years of experience in data science, analytics, or ML roles, including production-level model deployment.
Expertise in at least two areas of data science, managing projects end-to-end from technical implementation to stakeholder delivery.
Strong proficiency in Python or R for data manipulation, ML modeling, and NLP.
Expert-level SQL skills for large-scale data querying and analysis.
Experience with regression, clustering, anomaly detection, NLP, and conducting experiments/A-B tests.
Skilled in ML frameworks (scikit-learn, TensorFlow, PyTorch) and visualization tools (Tableau, Power BI, matplotlib, seaborn).
Solid understanding of statistics, hypothesis testing, and experimental design.
Strong communication and collaboration skills to influence technical and non-technical stakeholders.
Proven ability to mentor junior staff and lead projects that deliver measurable business impact.