Data Scientist

Enzo Tech Group; España; A distancia; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

A leading technology consulting firm is seeking a Mid-Senior level professional to rapidly prototype tree-based machine learning models for credit and risk modeling. The role is fully remote and requires collaboration with a distributed team. Ideal candidates will have strong experience with XGBoost, LightGBM, and proficiency in Python. This position focuses on early-stage experimentation and offers long-term extension potential.

Formación

• Strong hands-on experience with tree-based models.
• Proficient in Python for data science.
• Solid SQL skills for data preparation.
• Experience in cloud environments.
• Background in credit risk or financial services modelling.
• Ability to work in fast-paced prototyping environments.
• Strong English communication skills.

Responsabilidades

• Rapidly prototype tree-based machine learning models.
• Retrain existing credit risk models.
• Build new prototype credit models from scratch.
• Perform exploratory data analysis and feature testing.
• Provide insights on model performance.
• Collaborate with analysts and distributed team members.
• Focus on early-stage model development.

Conocimientos

Tree-based classification models (XGBoost, LightGBM, Random Forest)

Python for data science (Pandas, NumPy, scikit-learn)

SQL skills for data wrangling

Cloud environments (AWS, GCP, or Azure)

Credit risk, fraud risk, lending analytics

English communication skills

Descripción del empleo

Responsibilities

• Rapidly prototype tree-based machine learning models (XGBoost, LightGBM, Random Forest) to evaluate new external data sources.
• Retrain existing credit risk models with additional bureau, open banking, telco, or alternative datasets to measure incremental model lift.
• Build new prototype credit models from scratch using internal and external data.
• Perform exploratory data analysis, feature testing, and data value assessment.
• Provide insights on model performance, data quality, and predictive power.
• Work closely with a business analyst and collaborate with a small, distributed team.
• Focus exclusively on early-stage model development (no productionizing or MLOps).

Qualifications

• Strong hands‑on experience with tree-based classification models (XGBoost, LightGBM, Random Forest, Gradient Boosting).
• Proficiency in Python for data science (Pandas, NumPy, scikit‑learn).
• Solid SQL skills for data wrangling and dataset preparation.
• Experience working with cloud environments (AWS, GCP, or Azure).
• Background in credit risk, fraud risk, lending analytics, or financial services modelling.
• Ability to work in fast‑paced prototyping environments following an 80/20 approach.
• Strong English communication skills and ability to collaborate with remote team members.

Project Overview

Our client is building a new function focused on rapidly evaluating external data sources for use in credit and risk modelling. This position is dedicated to early‑stage experimentation, fast modelling cycles, and assessing whether new data sources improve predictive performance. Work is fully remote, requires overlap with EST/CST hours, and offers long‑term extension potential.

Apply

Apply directly or send your profile to [e-mail]

Seniority level

Mid‑Senior level

Employment type

Contract

Job function

Information Technology

Industries

IT Services and IT Consulting