Description
The organization develops data-driven solutions within a large financial organization. It brings together data science, software engineering, and business to turn complex datasets into scalable solutions for real-world applications.
Responsibilities
•Develop and productionize machine learning models
•Analyze large and complex datasets to identify patterns and opportunities
•Build data processing and feature engineering pipelines
•Develop Python-based data and machine learning solutions
•Collaborate with Data Engineers, Software Engineers, and business stakeholders
•Experiment with statistical and machine learning techniques
•Deploy, monitor, and improve models in production
•Contribute to MLOps and model lifecycle management
•Translate business challenges into scalable technical solutions
Requirements
•5+ years of experience in Data Science, Machine Learning, or a related field
•Strong Python skills
•Strong understanding of statistics and machine learning
•Experience with pandas, NumPy, and scikit-learn or similar frameworks
•Experience working with large datasets
•Experience bringing models into production
•Understanding of software engineering principles
•Experience working in multidisciplinary Agile teams
Nice to have
•Azure, Databricks or Spark, MLOps, MLflow or similar tooling
Conditions
No conditions stated in the posting.
