Data Scientist – Predictive Analytics, ML

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Enable Data

WebsiteLinkedInAll Job Openings

51 - 200 employees

☁️ SaaS

⚕️ Healthcare Insurance

🏢 Enterprise

SaaS • Healthcare Insurance • Enterprise

Enable Data is a company that offers modern IT solutions to empower its customers by leveraging innovative data analytics and cloud platforms to drive increased value across their business ecosystem. They specialize in the implementation of large-scale SAS applications, distributed rules engines for processing health-related data, and managing data ingest frameworks. Enable Data serves industries requiring advanced data analytics and IT solutions, with a particular focus on healthcare quality and big data management.

📋 Description

• Lead and mentor a team of data scientists and analysts; provide technical guidance and ensure high-quality deliverables. • Design, develop, and optimize machine learning models (classification, regression, clustering, forecasting, etc.). • Build and maintain big data processing pipelines using PySpark, Spark SQL, and distributed computing environments. • Architect and deploy scalable ML solutions on Azure (Azure Databricks, Azure ML, ADLS, ADF). • Oversee feature engineering, model lifecycle management, monitoring, and performance tuning. • Collaborate with cross-functional teams to translate business needs into analytical solutions. • Present insights, model outputs, and recommendations to technical and business stakeholders.

🎯 Requirements

• 10+ years of hands-on experience in data science and ML development. • Strong hands-on experience in leading complex analytical problem solving using traditional ML architecture (like supervised and unsupervised learning, time series and Deep learning) along with strong team leadership capabilities. • Expertise in Python, PySpark, scikit‑learn, XGBoost, and related ML libraries. • Strong experience with Azure data and ML services. • Solid understanding of distributed computing and performance optimization using Spark. • Proven ability to lead technical teams, conduct code reviews, mentor juniors, and manage project execution. • Excellent communication, stakeholder management, and problem‑solving skills. • Experience with MLOps practices and CI/CD pipelines.