Senior Data Scientist (Python)
Proxify Time zone: CET (+/- 3 hours)
Looking for a Remote Worldwide Development role? Senior Data Scientist (Python) at Proxify is listed on Makely Remote Jobs as a Full-time opening based in Time zone: CET (+/- 3 hours) (Worldwide). Review the role overview below, then apply on the employer’s original listing — Makely Remote Jobs does not process applications.
Skills
- data science
- power bi
- business intelligence
- python
- sql
Role overview
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. You will not just build prototypes in notebooks; you will design, train, evaluate, and deploy 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). We are unable to consider applications from candidates in other time zones.
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, so you can recharge
Enjoy up to 24 flex days off per year without losing pay, for full-time positions found through Proxify.
Career-accelerating positions at cutting-edge companies
Discover exclusive long-term remote positions at the world's most exciting companies.
Hand-picked opportunities, just for you
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.
Compensation
Enjoy the same pay, every month with positions landed through Proxify.
Summary provided for discovery. Always confirm details and apply on the original source. Makely Remote Jobs is not the employer and does not process applications.
Frequently asked questions
Is Senior Data Scientist (Python) at Proxify a remote job?
Yes. This listing is categorized as Remote Worldwide on Makely Remote Jobs. Confirm any location or timezone limits in the original posting before you apply.
What is the employment type for Senior Data Scientist (Python)?
Source data lists this as Full-time. Always verify the contract type, benefits, and start date on the employer’s application page.
Where is Senior Data Scientist (Python) located?
Listed location: Time zone: CET (+/- 3 hours). Many remote Development roles allow work-from-home with country or timezone restrictions — check the full description.
Do I apply on Makely Remote Jobs?
No. Makely Remote Jobs aggregates public remote job feeds for discovery. Use “Apply on Original Site” to open the employer’s official application URL. We never host applications or collect resumes.
Does Proxify list salary for this Development role?
Salary was not published in the source feed. Check the original listing or ask the recruiter during screening for compensation details.