Middle Data Scientist (Fintech)

TL;DR

Middle Data Scientist (Fintech): Building predictive models for trade execution, risk assessment, and market movement forecasting with an accent on developing and testing machine learning algorithms on real-time and historical financial data. Focus on integrating models into live trading environments and using tools like Python, TensorFlow, scikit-learn, Spark, and Airflow.

Location: In-office, hybrid, or remote flexibility

Company

An AI-first global tech company with 25+ years of engineering leadership.

What you will do

• Build predictive models for trade execution, risk assessment, and market movement forecasting
• Develop and test machine learning algorithms on real-time and historical financial data
• Work with large-scale datasets using BigQuery, Redshift, and Oracle
• Collaborate with engineering and quant teams to integrate models into live trading environments
• Use tools like Python, TensorFlow, scikit-learn, Spark, and Airflow to build and deploy models
• Participate in Agile ceremonies, story-pointing, and sprint reviews

Requirements

• Proficient in Python for data analysis and modelling (pandas, NumPy, scikit-learn, etc)
• Experience building models in financial domains (e.g. predictive analytics, anomaly detection, time series forecasting)
• Familiarity with cloud data platforms: GCP (BigQuery, Vertex AI) and/or AWS (S3, SageMaker)
• Solid understanding of SQL and relational databases (Oracle preferred)
• Exposure to model validation, backtesting, and deployment pipelines
• Strong statistics, probability, and quantitative reasoning skills

Nice to have

• Familiarity with alternative data (news sentiment, social media, satellite data)
• Experience with high-frequency or algorithmic trading models
• Knowledge of Kubernetes or containerised ML deployment pipelines
• Experience with MLOps tools (MLflow, Vertex AI Pipelines, etc)

Culture & Benefits

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement
• Well-being program
• Team events & local benefits