Machine Learning Engineer (Python) - EU-based only (offline)

About Puls Technologies GmbH:

Puls Project is at the verge of an exhilarating journey. Our mission is to create the entire financial world in one platform for German small to midsize enterprises and entrepreneurs, across all sectors and industries.
 

We are building a platform that will enable the customer to have money, where the customer needs it - just at the right time when they actually need it. The aim is to free up their time to make sure it can be spent on growing their business, not just managing to survive. Puls connects all your bank accounts in one place, business as well as private. The Customer will be able to have an overview of their financial history, as well as actually get forecasting for their cash flow with that data. The Customer will be able to make all payments in one place, instant and easy. And what if money gets tight? The future with Puls will give the opportunity to get business loans for SME without the hassle of a complicated bank checkup.

Key Responsibilities:

• Analyse large financial datasets using Python and Pandas.
• Develop and maintain machine learning models to predict financial metrics.
• Collaborate closely with our data scientists to enhance model accuracy and performance.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and insights in financial data.
• Ensure data quality, integrity, and consistency throughout the analysis process.
• Document and communicate findings and model performance to stakeholders.
• Stay up-to-date with the latest developments in data science and machine learning to continually improve our analytical capabilities.

Essential Skills and Experience:

• Proficient in Python with extensive experience in data analysis using Pandas or equivalent .
• Strong understanding of machine learning techniques and experience with libraries such as scikit-learn, TensorFlow, or PyTorch.
• Experience in building and optimising models for classification, regression, and clustering tasks.
• Solid understanding of statistical analysis and data visualisation techniques.
• Ability to work with large datasets and perform data cleaning, preprocessing, and transformation.
• Familiarity with version control systems like Git.
• Experience with SQL and database management is a plus.
• Experience with Prefect or similar orchestration tools for managing and automating data workflows.
• Strong problem-solving skills and ability to work independently.

Desirable Skills:

• Experience with time series analysis and financial data.
• Familiarity with cloud platforms such as AWS (Sagemaker), Google Cloud, or Microsoft Azure for deploying models.
• Understanding of natural language processing (NLP) techniques.

Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience).
• Minimum of 3 years of professional experience in data analysis and machine learning.
• Excellent communication skills and the ability to explain complex concepts to non-technical stakeholders.

Work Methodology:

• We use the Scrum framework to drive collaboration, adaptability, and continuous delivery.
• Regular participation in grooming sessions to refine and estimate the product backlog.
• Engage in iterative sprint cycles to ensure the timely delivery of high-quality features.

Working Hours:

• Our standard working hours are from 10:00 AM to 6:00 PM German time, Monday to Friday.

What We Offer:

• Competitive salary and benefits.
• Contribute to a fintech company that's making a real impact on how businesses manage their finances.