Build scalable data products, cloud-native data pipelines, and modern data platforms that support thousands of stores and millions of customer interactions.
Responsibilities
Design, develop, and support scalable data pipelines and data integration solutions.
Build data engineering solutions using Python, SQL, PySpark, and modern cloud technologies.
Develop and maintain trusted data products that enable analytics, reporting, operational intelligence, and AI use cases.
Contribute to enterprise data platforms built on Databricks, Apache Spark, and Lakehouse architectures.
Implement data quality, monitoring, testing, and observability capabilities to improve data reliability.
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Computer Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field.
Nice to have: Hands-on experience through coursework, internships, research, personal projects, or open-source contributions.
Nice to have: Familiarity with cloud platforms such as Azure, AWS, or Google Cloud Platform.
Nice to have: Exposure to Databricks, Apache Spark, Delta Lake, Airflow, dbt, Snowflake, or related technologies.
Nice to have: Experience using Git and modern software development tools.
Lead and architect advanced analytics and machine learning solutions within the Microsoft cloud ecosystem to support strategic decisions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack, ensuring alignment to enterprise data architecture and governance standards.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Principal‑level data scientist responsible for architecting, delivering, and governing enterprise‑grade advanced analytics and machine learning solutions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations. This position is not eligible for bonus or incentive compensation.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
The role will provide exposure to client execution, OTC derivative hedging, risk management, market analysis, inventory optimization, and collaboration with global trading and support teams.
Responsibilities
Support client-driven trading activities across APAC markets and assist with OTC derivative hedging during APAC trading hours.
Provide timely and accurate execution support to onshore and global hedge funds, institutional investors, and high-net-worth clients.
Monitor automated and algorithmic trading strategies, helping to ensure effective execution, appropriate risk controls, and accurate trade capture.
Assist with the management of market, liquidity, counterparty, and operational risks within established risk limits.
Support the development and enhancement of systematic tools for transaction analysis, trade monitoring, inventory management, and performance attribution.
Requirements
Bachelor’s degree and above in Finance, Economics, Mathematics, Statistics, Computer Science, Engineering, or a related discipline
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