Senior Data Scientist - Trading Analytics & ML Engineering

Key Responsibilities:

- Collaborate with business departments to translate requirements into effective machine learning solutions for our trading platform.

- Enhance existing models to improve accuracy, efficiency, and business value metrics across our trading ecosystem.

- Develop predictive algorithms that forecast user behavior patterns including churn probability, conversion rates, and lifetime value calculations.

- Transform prototype models into production-ready systems with robust data pipelines from preprocessing to prediction delivery.

- Conduct comprehensive exploratory data analysis on client behavior using Python 3.10+, SQL, and PySpark 3.4+.

- Design and implement automated tools to streamline the entire ML model lifecycle from development to deployment.

- Apply MLOps practices to ensure consistent quality, monitoring, and reliable deployment of machine learning models.

- Translate complex analytical findings into clear, actionable insights for non-technical stakeholders and business teams.

Required Skills:

- 1-3 years of professional experience building machine learning solutions with measurable business impact.

- Strong proficiency in Python and its data science ecosystem (NumPy, Pandas, Scikit-learn, XGBoost).

- Advanced SQL skills for querying, manipulating, and analyzing large financial datasets.

- Experience with Git for version control, collaborative development, and code review processes.

- Upper-intermediate or higher English proficiency in both written and verbal communication.

- Ability to work independently while maintaining clear communication in a remote environment.

- Solid understanding of statistical methods and their practical applications in predictive modeling.

- Bachelor's degree or higher in Computer Science, Statistics, Mathematics, or related quantitative field.