Lead Data Scientist job opportunity at Tiger Analytics Inc..

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Date2026-02-11T17:07:20.200Z bot
Tiger Analytics Inc. Lead Data Scientist
Experience: 8-years
Pattern: Full-time
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loacation Chicago, United States Of America
loacation Chicago....United States Of America

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. We are seeking a highly skilled and experienced Lead Data Scientist with strong expertise in forecasting models, including ARIMA, time series modeling, and PMPM forecasting, preferably within the healthcare domain. The ideal candidate will have a proven track record of designing, developing, and deploying scalable forecasting solutions, while leading projects and mentoring teams. This role requires deep technical expertise, hands-on coding experience, and the ability to collaborate closely with clients and stakeholders to translate business needs into robust analytical solutions. Key Responsibilities Design, develop, and deploy advanced forecasting models (ARIMA, SARIMA, Prophet, and other time series techniques) for healthcare-related use cases including PMPM forecasting. Analyze structured and large-scale healthcare datasets (claims, membership, utilization, cost data) to generate actionable insights. Build scalable, production-ready ML pipelines and automate forecasting workflows. Perform model validation, back-testing, hyperparameter tuning, and performance monitoring to ensure accuracy and stability. Translate business problems into data science solutions and clearly communicate findings to clients and stakeholders. Lead end-to-end project execution, mentor junior data scientists, and ensure best practices in modeling and MLOps. Collaborate cross-functionally with engineering, product, and business teams to drive data-driven decision-making. Collaborate, coach, and learn with a growing team of experienced Data Scientists. 6–8 years of experience in Data Science, Machine Learning, or Advanced Analytics. Strong expertise in time series forecasting techniques such as ARIMA/SARIMA, exponential smoothing, and other statistical models. Hands-on experience in PMPM forecasting and healthcare analytics (claims, cost, utilization data preferred). Proficiency in Python (pandas, numpy, stats models, scikit-learn) and SQL for data analysis and modeling. Experience in deploying models to production and building automated data pipelines (MLOps exposure preferred). Strong understanding of statistical concepts, model evaluation metrics (MAPE, RMSE, etc.), and model interpretability. Excellent communication skills with experience engaging business stakeholders or clients. Proficiency in building data pipelines using tools such as Airflow, Databricks, Spark, or similar frameworks. Experience working in agile environments with cross-functional collaboration.

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