Data Ops Scientist, Development — ML & Predictive Analytics

Citrin-Cooperman-Advisors-LLC; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

Citrin Cooperman is seeking a Data Operations Scientist to own core predictive analytics and ML capabilities within the Development team of Information Technology. You will design, train, and deploy models for churn, demand forecasting, and optimization using Python, PySpark, and the Microsoft Fabric ecosystem.

The role emphasizes pragmatic modeling, model interpretability, and production deployments with MLOps discipline, collaborating with BI developers to embed outputs into Power BI

Qualifications

• Bachelor’s degree in computer science, data engineering, mathematics, or equivalent practical experience.
• 3–5 years of professional experience as a Data Scientist, Machine Learning Engineer, or Advanced Analyst in a corporate environment.
• Deep proficiency in Python and SQL, with libraries such as Pandas, NumPy, Scikit-Learn, PyTorch or TensorFlow.

Responsibilities

• Design, train, and validate traditional machine learning models (regression, classification, clustering, time-series) using Python and PySpark.
• Collaborate with Data Engineers to shape the Gold data layer and robust feature pipelines for training and inference.
• Deploy models in production within the Microsoft Fabric ecosystem and manage MLOps pipelines (MLflow, drift monitoring, retraining).
• Conduct Exploratory Data Analysis on enterprise datasets to validate hypotheses and inform decisions.
• Translate statistical outcomes into actionable insights for stakeholders and integrate model outputs into dashboards.

Skills

Python

SQL

Pandas

NumPy

Scikit-Learn

PyTorch/TensorFlow

MLOps

Model Evaluation Metrics

Stakeholder Communication

Education

Bachelor's degree in CS/Math or equivalent

Tools

MLflow

Databricks

Azure Machine Learning

Apache Spark

PySpark

Job description

Citrin Cooperman is seeking a Data Operations Scientist to own core predictive analytics and ML capabilities within the Development team of Information Technology. You will design, train, and deploy models for churn, demand forecasting, and optimization using Python, PySpark, and the Microsoft Fabric ecosystem.

The role emphasizes pragmatic modeling, model interpretability, and production deployments with MLOps discipline, collaborating with BI developers to embed outputs into Power BI