Data Scientist (f/m/x)
Heidelberg, Baden-Württemberg, Germany (Hybrid) · Full Time
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- Experience
- 3–5 yrs
- Salary
- —
- Openings
- 1
- Posted
- 1 week ago
- Work mode
- Hybrid
- Resume
- Required to apply
Where you'll work
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Job description
Role Overview
Join paretos to drive the application of cutting-edge technology and support our mission to rethink decision-making. As part of our expert tech team, you will help build the machine-learning backbone of our product, primarily focusing on time-series forecasting.
Key Responsibilities
- Coordinate and actively contribute to new machine-learning features, shaping the product roadmap and decisions by understanding business challenges and proposing practical solutions.
- Lead testing of new predictive modeling methods and develop new or improve existing machine-learning and deep-learning models to meet product needs.
- Collaborate closely with a diverse, motivated team, sharing insights on machine-learning and engineering concepts, and provide mentorship to colleagues with your expertise.
- Utilize customer data daily to identify business and product opportunities to drive strategic value.
- Apply strategic thinking in product and feature development to generate tangible business value.
Candidate Profile
- 3 to 5 years of professional experience in data science products, emphasizing hands-on technical responsibility.
- Advanced proficiency in Python programming.
- Practical experience with modeling techniques, including machine learning, deep learning, and time-series modeling.
- Strong skills in data analysis and modeling in Python, covering data preprocessing, cleaning, and exploratory data analysis.
- Solid understanding of mathematical problem formulation and solution approaches.
- Experience with key data-science libraries such as pandas, polars, and numpy.
- Familiarity with machine-learning libraries like scikit-learn, PyTorch, and XGBoost.
- Track record of implementing and deploying ML products into production environments.
- Motivation to collaborate within a team of talented professionals.
- Fluency in both English and German.
- Bonus: experience in operations research (OR) is advantageous.
Work Setup
This position is hybrid-based, requiring 1-2 days per week at our Heidelberg office, working closely with product managers, forward deployed/AI engineers, and data scientists.
Benefits
- Remote-first culture with the option to work from our scenic Heidelberg office anytime.
- Personal learning budget to advance your professional development, including participation in "Journal Clubs" discussing latest AI advancements.
- Join a highly skilled and motivated team that enjoys working together.
- Regular technical and social events, both online and in-person.
- Provision of necessary office equipment to enable your peak performance.
- Flexible working hours tailored to your preferences.
- Mobility budget supporting various transport options to reduce your carbon footprint.
- Bring your dog to the office as part of our "paretos Dog Club".
- Enjoy premium coffee brewed in-office and have opportunities for social coffee chats, with the chance to earn the title of "paretos Office Barista of the Year" at our Christmas party.
Additional Information
paretos uses AI tools to assist preliminary candidate screening; however, all interview invitations are decided by humans. We pride ourselves on being an inclusive employer, promoting equal opportunities, and encourage applicants to apply even if they don’t meet every requirement fully.
About paretos
paretos is a leading AI-powered decision intelligence platform enabling effective, data-driven decisions across organizations. Our Business Agents analyze complex datasets, forecast scenarios, and derive optimal actions — from demand forecasting and inventory replenishment to high-level strategic decisions — all through a no-code interface accessible to users without data science expertise. Our culture is grounded in GUNG HO principles: meaningful work, shared goals, and mutual support, bringing together passionate, high-performing, and caring individuals from diverse genders, cultures, and backgrounds.