Data Scientist - Predictive Analytics & ML

Enable Data Incorporated; United States; Remote; USD 170,000 - 230,000; Full time

Job summary

Enable Data Incorporated is seeking a Data Science Lead to guide a team of data scientists and analysts, shaping strategy and technical direction. You will design and deploy ML solutions on Azure, build scalable pipelines with PySpark, and translate business requirements into actionable analytics.

The role requires outstanding communication and the ability to mentor senior and junior teammates while delivering impactful insights for business decisions.

Qualifications

• 10+ years of hands-on data science experience.
• Proven leadership of complex analytics teams.
• Expertise in Python, PySpark, and ML libraries.
• Experience with Azure data/services.

Responsibilities

• Lead and mentor a team of data scientists and analysts.
• Design, develop, and optimize ML models (classification, regression, forecasting, etc.).
• Build and maintain big data pipelines using PySpark and Spark SQL.
• Architect and deploy scalable ML solutions on Azure.
• Oversee feature engineering, model lifecycle management, and monitoring.
• Collaborate with cross-functional teams to translate business needs.
• Present insights, model outputs, and recommendations to stakeholders.

Skills

Leadership

Data science

Python

PySpark

ML libraries

Azure ML

Spark

Time series

Deep learning

MLOps

Job description

Data Science Lead (Predictive Analytics & ML)

Key Responsibilities

• 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.

Required Skills

• 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.