Job Overview

Job Title Data Scientist
Hiring Organization BeetsBytes
Company Website https://www.beetsbytes.com/
Remote Locations Worldwide
Job Type Remote, Full-Time

We are looking for a Data Scientist to join our Data Science and Engineering Team. This is an exciting opportunity to work on customer-driven projects in the field of municipal heat planning, where you will play a critical role in understanding, transforming, and integrating data into proprietary systems. You will work closely with project managers and customers to ensure data is processed and visualized according to specific requirements, with a focus on delivering actionable insights. This role requires a blend of data science, engineering, and strong problem-solving skills.

Job Responsibilities

Data Understanding & Preparation:

Understand and process data related to municipal heat planning. Cleanse, integrate, and align customer data, ensuring proper formatting and consistency.

Algorithm Adjustments & Data Integration:

Adjust Python code within proprietary algorithms used in the heat model to accommodate customer-specific requirements and new heat technologies (using predefined templates). You will ensure data flows smoothly and that results are accurate.

Data Modelling & Visualization:

Trigger models to generate actionable results, such as diagrams and data prepared for dashboards. Use visualization tools to communicate insights effectively and to make data accessible to non-technical stakeholders.

Collaboration & Communication:

Work closely with project managers and customers to gather requirements, review feedback, and adapt the results as necessary. A few customer projects may run simultaneously, each project will have its own Jira epic, and Kanban methodology will be used for task management and progress tracking.

Job Requirements

Technical Skills:

Python Programming
Extensive experience with Python data packages (e.g., numpy, pandas, scikit- learn, etc.)
Experience with data engineering tools (especially Airflow and dbt)
Extensive experience with databases (especially Postgres, duckdb, and Snowflake)
Visualization and evaluation of results in Superset – is a plus
Selection of appropriate tools for data visualization – is a plus

Methodological Competence:

Execution of data science projects and data analysis
Targeted method selection
Targeted method selection (again listed, could be a redundancy) – Methods for pattern recognition – is a plus
Development and deployment of algorithms