Senior Data Scientist Python - MLOps & Cloud ML Lead in Columbus
Career & Market Insight
Senior-Level Role with Strong Production ML Focus
This is not a research-heavy data science role — it explicitly prioritizes production ML engineering: Docker, microservices, cloud ML platforms, and CI/CD for models. That hybrid profile (Data Scientist + ML Engineer) is among the highest-demand skill sets in 2024–2025, commanding $130K–$180K+ at direct employers. As a Proxify contractor, compensation isn't disclosed here, so negotiate assertively.
Skills you'll develop or deepen:
- End-to-end MLOps (MLflow, DVC, SageMaker, Vertex AI)
- Distributed computing at scale (PySpark, Ray)
- Production Python architecture and code review leadership
- Cross-functional communication: translating model metrics to business outcomes
Green flags:
- Proxify has strong independent ratings (Glassdoor 4.5, Trustpilot 4.8) — rare for contractor platforms
- 24 flex days off annually is generous for a contractor arrangement
- Long-term positions mean less context-switching than typical freelance gigs
Yellow flags:
- Salary is undisclosed — typical for network/agency models, but you're negotiating without benchmarks
- You work "through" Proxify with an unnamed client — less direct career brand-building
- The technical lead framing suggests high ownership; confirm team size and support structure before accepting
About Us
Talent has no borders. Proxify's mission is to connect top developers around the world with the opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction. 🙂
Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 5000+ talented developers trust Proxify and its network to fulfill their dreams and objectives.
Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.
The Role
We are looking for a Senior Data Scientist (Python) to join one of our high-growth client teams as a technical lead in data innovation. In this role, you will be responsible for transforming complex, high-velocity datasets into predictive models and actionable systems that directly influence product strategy and business operations.
You will bridge the gap between pure research and production software engineering — not just building prototypes in notebooks, but designing, training, evaluating, and deploying robust machine learning models into live cloud environments. This is a role for a systems-thinking data scientist who values clean, modular Python architecture, statistical rigor, and scalable data pipelines.
What We Are Looking For
- 5+ years of professional experience as a Data Scientist, with expert-level mastery of the Python data ecosystem (Pandas, NumPy, SciPy, Scikit-Learn).
- Deep theoretical and practical knowledge of supervised and unsupervised learning, regression, classification, clustering, and time-series forecasting.
- Proven track record of moving models out of Jupyter Notebooks and into production environments using containerization (Docker) and microservice design.
- Strong proficiency in writing complex, optimized SQL queries and experience handling large-scale data using distributed computing frameworks like PySpark or Ray.
- Experience with machine learning lifecycle tools (such as MLflow, DVC, or Weights & Biases) for model tracking, versioning, and feature store management.
- Hands-on experience leveraging cloud data infrastructure (AWS, GCP, or Azure) and managed ML services (e.g., SageMaker or Vertex AI).
- Time zone: CET (± 3 hours). Applications from candidates outside this time zone cannot be considered.
Nice-to-Have
- Deep Learning experience using PyTorch or TensorFlow/Keras.
- Experience with NLP frameworks (Hugging Face, spaCy) or deploying LLM-based pipelines (LangChain, vector databases).
- Familiarity with orchestration tools like Apache Airflow or Prefect.
- Strong background in experimental design, A/B testing methodologies, and statistical significance validation.
Responsibilities
- Design, build, and optimize scalable predictive models and machine learning algorithms to solve complex business challenges.
- Architect and maintain robust data pipelines and feature sets, ensuring data quality, consistency, and integrity across training and inference layers.
- Partner with Data Engineers, Product Managers, and Backend Teams to integrate ML models seamlessly into core application APIs.
- Conduct rigorous peer code reviews for data science workflows, championing production-grade Python design patterns and linting standards.
- Translate highly technical metrics (Precision, Recall, ROC-AUC, RMSE) into clear business outcomes and executive-level recommendations.
What We Offer
- Get paid, not played: No more unreliable clients. Enjoy on-time monthly payments with flexible withdrawal options.
- Predictable project hours: Enjoy a harmonious work-life balance with consistent 8-hour working days with clients.
- Flex days to recharge: Up to 24 flex days off per year without losing pay, for full-time positions found through Proxify.
- Career-accelerating positions: Discover exclusive long-term remote positions at the world's most exciting companies.
- Hand-picked opportunities: Skip the typical recruitment roadblocks and biases with personally matched positions.
- One seamless process, multiple opportunities: A one-time contracting process for endless opportunities, with no extra assessments.
- Consistent compensation: Enjoy the same pay, every month with positions landed through Proxify.
Frequently Asked Questions
Is this role fully remote or office-based?
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