Wandoo Finance is hiring a Data Scientist!

 

Fintech is a very dynamic environment. Things change all the time. We grow, develop and enter new markets. It also means more challenges for our Data Science team. New models, adjustments, innovations! That is where you come into play! You already have hands-on Data Science expertise. You have seen things. Built efficient machine learning models and integrated them into pipelines. Ensured performance and scalability. Efficiently.

 

But you would like to do more. To make things happen. And not just to start them but to finish them with flair. You can work independently and in a team. You thrive in an environment with minimum bureaucracy where the decisions are made fast. And to have a lot of impact.

 

And the last thing. A cherry on the cake. You feel that you can do more. To work with a great team. To do your best work. If so What are you waiting for? Apply!

·       Develop and maintain automated machine learning pipelines

·      Extract data from various sources (data warehouses, production databases, third-party providers, public datasets)

·      Feature engineering, including statistical feature generation, time-series extraction, and feature evaluation/cleaning

·      Automate model training, hyperparameter tuning, and feature selection

·       Generation and comparison of model metrics for evaluation

·      Streamline their deployment and ensure continuous monitoring of model performance

·      Prototype machine learning models using best practices in feature engineering, model selection, and validation with frameworks such as Scikit-learn, PyTorch, and H2O

·      Communicate findings, analyses, and model results to key stakeholders through presentations and reports

·      Draft recommendations to optimize product performance and underwriting policies

·      Maintain and update intuitive dashboards for evaluating model metrics and customizing model settings

·      Bachelors Degree in Computer Science, Data Science, Statistics, or a related field

·      3+ years of experience developing traditional machine learning models using Python and any of the ML frameworks

·      Time-Series Expertise: Demonstrated experience in analyzing and using time-series data for machine learning models

·      Tech Stack: Proficient with FastAPI, RabbitMQ, Docker, and PostgreSQL

·      ML Pipeline Automation: Proven experience building data science pipelines using Airflow

·      Monitoring & Maintenance: Experience with monitoring machine learning models (Population stability, feature stability, SHAP)

·      Modeling Expertise: Hands-on experience with GBM, XGBoost, and related tree/boosting algorithms

·      Experience with Google cloud

·       Prior experience with Java and Spring Boot is a bonus

·      Competitive remuneration package, with a gross monthly salary ranging from 4500 to 6500 EUR and performance-based bonuses

·      Collaborative and inclusive work environment

·      Professional and highly engaged team

·      Flexible working hours and remote work options

·      Health insurance and covered phone bills

·      Modern and spacious office with a fully stocked kitchen and free parking

·      Participation in company-sponsored events

·      Professional development and education relevant to professional growth