[Hiring] Senior Data Scientist @mazzatech

Role Description

The Data Science / ML team is a global group working on advances in machine learning and applied statistical methods for real-world evidence. Our work spans:

• Disease detection
• Patient outcome prediction
• Retrospective clinical studies
• Patient subgroups discovery

We are looking for a creative, intellectually curious Data Scientist / AIML Engineer to join our Healthcare Data Science team. This role supports both ML delivery and analytics delivery:

• Develop ML solutions on large-scale medical data for disease detection and patient outcome prediction.
• Translate client requirements for patient identification and HCP targeting into production analytics deliverables.
• Prove out new methodology and capabilities on live client delivery, then partner with engineering and product to productionize and scale what works.
• Contribute to AI/ML enablement proofs of concept that enhance existing offerings or shape new ones for our healthcare and pharma clients.

Qualifications

• Experience working on creating machine learning algorithms in the healthcare and/or commercial Pharma industries.
• Experience working with large, real-world datasets including US open medical claims, ambulatory EMR, and consumer data.
• Experience mentoring junior machine learning engineers.
• Knowledge of supervised machine learning methods, such as regularized regressions, ensemble tree classifiers (e.g. XGBoost), support vector machines, etc.
• Good understanding of classical statistical methods, such as fitting regression models, inference testing, and sampling.
• Proficiency in Python, including OOP, to support ML and ETL pipelines.
• Understanding coding practices and version control software such as Git.
• Ability to write clean and efficient code and a good understanding of the Data Science package landscape.
• Excellent communication skills, both verbal and written.
• A proactive, innovative, and pragmatic approach to problem solving.
• Ability to think critically and independently, and work as part of a cross-functional team.

Requirements

• Experience with high volume data sets that benefit from parallel computation, such as with Pyspark/Spark.
• Knowledge of healthcare/life science issues involving Real-World Evidence.
• Experience with production pipelines that power recurring client deliverables at cadence.
• Experience translating epidemiologic, clinical, or commercial rule sets into scalable code on claims or EMR data.
• Experience developing agentic solutions to workflow automation and data-driven insights.
• Experience with Databricks and/or Snowflake.

Benefits

• Experience on NLP applications, Deep learning, Pharma Analytics, Machine Learning techniques like regression, classification, predictive modeling, clustering, forecasting.
• Experience working on various Python libraries for Exploratory data analysis, Feature Engineering, and Model building.
• Good to have knowledge of GenAI, LLMs, model fine tuning, and deployment.