Senior Data Scientist - Remote ML Lead & Production

Proxify; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Get paid, not played

On-time monthly payments

Flexible withdrawal options

Predictable project hours

8-hour workdays with clients

Flexible days off

Long-term remote positions

Personally matched positions

Job summary

Proxify is seeking a Senior Data Scientist (Python) to lead data innovation for a high-growth client team. You will transform complex data into predictive models and deploy robust ML solutions in live cloud environments.

You will bridge research and production, emphasizing modular Python design, statistics, and scalable pipelines. You will guide ML projects from prototyping to production at scale.

Qualifications

• 5+ years of professional data science experience with Python data ecosystem.
• Experience moving models from notebooks to production with Docker and microservices.
• Strong SQL skills and ability to handle large datasets with distributed frameworks.
• Experience with ML lifecycle tools for model tracking and feature stores.
• Hands-on cloud experience with AWS, GCP, or Azure and managed ML services.

Responsibilities

• Design, build, and optimize scalable predictive models and ML algorithms.
• Architect and maintain robust data pipelines and feature sets.
• Collaborate with engineers, product managers, and backend teams to deploy models.
• Lead peer reviews and promote production-grade Python patterns.
• Translate metrics into actionable business outcomes for leadership.

Skills

Python

SQL

Pandas

NumPy

SciPy

Scikit-Learn

Docker

PySpark

Ray

MLflow

DVC

Weights & Biases

AWS

GCP

Azure

SageMaker

Vertex AI

Tools

Docker

PySpark

Ray

MLflow

DVC

Weights & Biases

SageMaker

Vertex AI

Job description

Proxify is seeking a Senior Data Scientist (Python) to lead data innovation for a high-growth client team. You will transform complex data into predictive models and deploy robust ML solutions in live cloud environments.

You will bridge research and production, emphasizing modular Python design, statistics, and scalable pipelines. You will guide ML projects from prototyping to production at scale.