This is a remote position.
We are seeking a Machine Learning Engineer to join our team and work on a project centered on multi-year transactional data analysis and predictive modeling. This role offers the opportunity to directly impact client decision-making by uncovering hidden patterns in data, generating forecasts, and deploying models that drive measurable business outcomes.
You will work with a consultancy with over 20 years of experience helping organizations transform challenges into growth opportunities, specialized in data-driven problem solving, identifying inefficiencies, and enabling businesses to scale through strategic insights and cost reduction initiatives.Key Responsibilities
Receive, clean, and preprocess large volumes of transactional and financial data
Design, train, and optimize predictive models to identify trends, clusters, and anomalies
Generate forecasts and actionable insights to support business strategies
Collaborate with data engineers and consultants to integrate models into production systems
Contribute to hypothesis-driven problem solving and help shape data-backed strategies for clients
Requirements
- Strong proficiency in Python, with libraries such as Pandas, NumPy, and Scikit-learn
- Hands-on experience with machine learning models (e.g., XGBoost, Random Forest)
- Knowledge of model interpretability and explainability techniques (decision trees, SHAP, or LLM-based explanations)
- Analytical mindset with a solid business-oriented problem-solving approach
- Ability to translate complex datasets into clear, strategic recommendations
- Intermediate English
Desirables
- Experience with LLMs (Large Language Models) and workflow automation tools such as n8n
- Familiarity with Java and Node.js for building and maintaining data pipelines
- Experience with data extraction, API integrations, and implementing return triggers to source systems