Data Scientist

isolved; Phoenix (AZ); Hybrid; USD 90,000 - 120,000; Full time

Benefits offered by this job

Collaborative environment

Innovative use of AI/ML

Opportunity to impact business directly

Job summary

A leading HCM provider is seeking a skilled Data Scientist to develop and implement predictive models aimed at customer retention and revenue growth. You will leverage Databricks for building scalable data models, applying machine learning techniques, and translating complex data into actionable business insights. The ideal candidate has a Master's or PhD and over 3 years in data science, strong skills in Python and SQL, and experience in customer lifecycle analytics. This opportunity is located in Phoenix, Arizona.

Qualifications

• Master's or PhD in a related field or equivalent industry experience.
• 3+ years of experience building predictive models in production.
• Strong proficiency in Python and SQL.

Responsibilities

• Design and deploy predictive models using Databricks.
• Build scalable data pipelines in Databricks.
• Translate analytical outputs into recommendations.

Skills

Python (pandas, scikit-learn, PySpark)

Customer lifecycle analytics

Databricks

SQL

Education

Master's or PhD in Data Science, Statistics, Computer Science

Tools

Databricks

MLflow

PySpark

Job description

We are seeking a highly skilled Data Scientist to focus on building and deploying predictive models that identify customer churn risk and upsell opportunities. This role will play a key part in driving revenue growth and retention strategies by leveraging advanced machine learning, statistical modeling, and large‑scale data capabilities within Databricks.

Why Join Us?

• Be at the forefront of using Databricks AI/ML capabilities to solve real‑world business challenges.
• Directly influence customer retention and revenue growth through applied data science.
• Work in a collaborative environment where experimentation and innovation are encouraged.

Core Job Duties

Model Development

• Design, develop, and deploy predictive models for customer churn and upsell propensity using Databricks ML capabilities.
• Evaluate and compare algorithms (e.g., logistic regression, gradient boosting, random forest, deep learning) to optimize predictive performance.
• Incorporate feature engineering pipelines that leverage customer behavior, transaction history, and product usage data.

Data Engineering & Pipeline Ownership

• Build and maintain scalable data pipelines in Databricks (using PySpark, Delta Lake, and MLflow) to enable reliable model training and scoring.
• Collaborate with data engineers to ensure proper data ingestion, transformation, and governance.

Experimentation & Validation

• Conduct A/B tests and back testing to validate model effectiveness.
• Apply techniques for model monitoring, drift detection, and retraining in production.

Business Impact & Storytelling

• Translate complex analytical outputs into clear recommendations for business stakeholders.
• Partner with Product and Customer Success teams to design strategies that reduce churn, increase upsell, and improve customer retention KPIs.

Minimum Qualifications

• Master's or PhD in Data Science, Statistics, Computer Science, or related field (or equivalent industry experience).
• 3+ years of experience building predictive models in a production environment.
• Strong proficiency in Python (pandas, scikit‑learn, PySpark) and SQL.
• Demonstrated expertise using Databricks for data manipulation and distributed processing with PySpark, building and managing models with MLflow, leveraging Delta Lake, and implementing scalable ML pipelines within Databricks' ML Runtime.
• Experience with feature engineering for behavioral and transactional datasets.
• Strong understanding of customer lifecycle analytics, including churn modeling and upsell/recommendation systems.
• Ability to communicate results and influence decision‑making across technical and non‑technical teams.

Preferred Qualifications

• Experience with cloud platforms (Azure Databricks, AWS, or GCP).
• Familiarity with Unity Catalog for data governance and security.
• Knowledge of deep learning frameworks (TensorFlow, PyTorch) within Databricks.
• Exposure to MLOps best practices (CI/CD for ML, model versioning, monitoring).
• Background in SaaS, subscription‑based businesses, or customer analytics.

Physical Demands

Prolonged periods of sitting at a desk and working on a computer. Must be able to lift up to 15 pounds.

Travel Required

Limited.

Work Authorization

Employees must be legally authorized to work in the United States.

FLSA Classification

Exempt.

Location

Any.

Effective Date

9/16/2025.

About Isolved

isolved is a provider of human capital management (HCM) solutions that help organizations recruit, retain and elevate their workforce. More than 195,000 employers and 8 million employees rely on isolved's software and services to streamline human resource (HR) operations and deliver employee experiences that matter. isolved People Cloud™ is a unified yet modular HCM platform with built‑in artificial intelligence (AI) and analytics that connects HR, payroll, benefits, and workforce and talent management into a single solution that drives better business outcomes. Through the Sidekick Advantage™, isolved also provides expert guidance, embedded services and an engaged community that empowers People Heroes™ to grow their companies and careers. Learn more at www.isolvedhcm.com.

isolved is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.