Senior Data Scientist

Gdansk, Poland

Job Reference 1251862

Location Gdansk, Poland

Industry IT - Cloud & Infrastructure

Function IT & Telecoms

Job Type Contract

Date Added November 27, 2024

Python Developer

 

Location: Poland (Remote)

Contract: 6 Months +

Start: ASAP

Key Skills: Innovation | Machine Learning | Data Insights | Real-time Processing | Collaboration | Python | Model Deployment | Docker | Mentorship |

 

Key Responsibilities:

 

  • Generate innovative ideas and develop compelling business cases, presenting them effectively to stakeholders.
  • Analyze complex datasets to uncover actionable insights, translating findings into strategic recommendations.
  • Communicate data-driven insights through clear verbal presentations and impactful visualizations tailored to diverse audiences.
  • Collaborate with cross-functional teams to establish and implement success metrics, ensuring alignment with product objectives and stakeholder needs.
  • Develop, implement, and fine-tune machine learning models that are scalable, reliable, and efficient for real-time predictions.
  • Partner with Machine Learning Engineers to deploy and maintain models while driving performance enhancements.
  • Work with real-time data, seamlessly integrating it into machine learning frameworks to optimize predictions.
  • Collaborate with Developers and Operations Research Scientists to ensure effective utilization of predictions for operational impact.
  • Foster collaboration within the data science team by sharing best practices, providing feedback, and driving continuous improvement.

 

Experience:

 

  • Expertise in data science and machine learning methodologies, with proven experience applying them in production settings.
  • Demonstrated success in deploying, scaling, and maintaining machine learning models for long-term use.
  • Proficiency in Python (e.g., scikit-learn, pandas, seaborn) and SQL for data analysis and production applications.
  • Strong grasp of software development practices, including testing, version control (git), code reviews, and lifecycle management for models.
  • Familiarity with Docker containers for creating reproducible and scalable environments.
  • Experience integrating real-time data into machine learning pipelines and frameworks.

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