Junior Python Developer

Salt; Nürnberg; Hybrid; EUR 40.000 - 65.000; Vollzeit

Zusammenfassung

A leading company in data analytics is looking for a Junior Python Developer to assist in processing and analyzing complex lab data for sports scientists. The freelance role involves developing Python solutions, integrating algorithms, and utilizing tools like Matplotlib and Plotly. This position offers the opportunity to work in a dynamic environment on cutting-edge projects for a duration of 6 months with hybrid working conditions.

Qualifikationen

• Experience with Python programming.
• Ability to process and analyze complex time-series data.
• Familiarity with REST-API and data visualization tools.

Aufgaben

• Implement pipelines to process raw data from lab equipment.
• Convert and resample data while ensuring proper integrations.
• Create visualizations for sports scientists using advanced frameworks.

Kenntnisse

Python

Data Processing

REST-API

Time-series Data Analysis

Matplotlib

Plotly

C/C++

Jobbeschreibung

Salt is currently hiring a Junior Python Developer for a client in Germany.

The role is freelance, lasting 6 months, with 2 days in the office per week. The candidate should be able to start ASAP.

Job Responsibilities

1. Implement specified pipelines to process raw data from lab equipment.
2. Develop in Python; some C/C++ coding or integration may be required depending on computational complexity.
3. Process and analyze complex time-series data.
4. Convert data into different coordinate systems.
5. Resample data to account for sampling rate differences.
6. Integrate algorithms with software from various lab-machine vendors.
7. Use REST-API to upload processed data into our ADM system.
8. Deploy pipelines as needed: either integrate into the "Plotly-dash" application or as a Notebook on Databricks.
9. Create visualization approaches for interpretability by sports scientists, utilizing Matplotlib/Plotly and 3D rendering frameworks.
10. Implement data-fusion methods, including time-wise registration of data from multiple sources with varying sample rates and registration of datasets in different spaces.