About the Role
We’re looking for a Data Scientist to build and deploy advanced predictive models that reduce customer churn and identify upsell opportunities. You’ll work with Databricks AI/ML capabilities to turn massive datasets into actionable insights, driving revenue growth and retention strategies.
This role is ideal for someone who loves solving complex business problems with data and wants to see their work make a direct impact on growth and customer experience.
Why Join Us
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Innovate at scale – use cutting-edge Databricks ML & AI tools to solve real-world business challenges.
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Drive measurable impact – your models will directly influence retention, upselling, and customer success.
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Collaborative, supportive culture – work with experts across Data Engineering, Product, and Customer Success.
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Professional growth – access advanced tools, resources, and ongoing learning opportunities.
Key Responsibilities
Model Development
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Design, build, and deploy predictive models for customer churn and upsell propensity.
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Experiment with algorithms such as logistic regression, gradient boosting, random forest, and deep learning.
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Engineer features from customer behavior, transaction history, and usage patterns.
Data Engineering & Pipelines
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Build and maintain scalable data pipelines in Databricks (PySpark, Delta Lake, MLflow).
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Partner with Data Engineers to ensure clean, governed, production-ready datasets.
Experimentation & Model Validation
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Run A/B tests and backtesting to validate predictive performance.
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Monitor model drift and implement retraining pipelines for production models.
Business Impact & Communication
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Translate complex analytics into clear, actionable recommendations for stakeholders.
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Partner with Product & Customer Success teams to shape retention and upsell strategies.
Minimum Qualifications
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Master’s or PhD in Data Science, Statistics, Computer Science, or related field (or equivalent experience).
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3+ years of experience developing and deploying predictive models in production.
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Advanced skills in Python (pandas, scikit-learn, PySpark) and SQL.
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Hands-on expertise with Databricks, including:
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Distributed data processing (PySpark)
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MLflow for model management
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Delta Lake for efficient storage & retrieval
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Building scalable ML pipelines
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Strong understanding of customer lifecycle analytics (churn, upsell, recommendation systems).
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Excellent communication skills to explain insights to non-technical stakeholders.
Preferred Qualifications
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Experience with cloud platforms (Azure Databricks, AWS, GCP).
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Familiarity with Unity Catalog for data governance & security.
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Experience with deep learning frameworks (TensorFlow, PyTorch) inside Databricks.
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Knowledge of MLOps best practices (CI/CD, model versioning, monitoring).
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Background in SaaS or subscription-based businesses.
About isolved
isolved provides human capital management (HCM) solutions to 195,000+ employers and 8M+ employees, helping organizations streamline HR, payroll, benefits, and talent management. Our AI-powered People Cloud™ platform and Sidekick Advantage™ services empower businesses to create better employee experiences and drive long-term success.
Learn more: www.isolvedhcm.com/careers
Compensation & Benefits
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Competitive salary (base + performance incentives).
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Comprehensive benefits: Medical, Dental, Vision, Life Insurance, PTO.
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Long-term incentives (e.g., equity grants) for eligible roles.
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Transparent & fair compensation practices — full details provided during the finalist stage.
isolved is an Equal Opportunity Employer. We celebrate diversity and welcome applicants of all backgrounds, abilities, and identities.