Role
Mid-Level Data Scientist – Financial Services
Job Overview
We are looking for a skilled and motivated Mid-Level Data Scientist to join our analytics team, with a focus on the banking, payments, or financial technology sectors. The ideal candidate will have 3–5 years of experience in data science or analytics, along with a strong foundation in statistical modeling, machine learning, and data programming. You’ll work collaboratively with business and technical stakeholders to analyze data and build predictive models that inform key decisions and improve business performance.
Key Responsibilities
- Develop and apply machine learning models and statistical analyses to solve real-world problems in the banking and payments industries.
- Work with large datasets using tools such as SQL, Python, R, or SAS to clean, manipulate, and derive meaningful insights.
- Use a variety of statistical and machine learning techniques including Linear & Logistic Regression, Decision Trees, Random Forests, Clustering, and PCA.
- Build, test, and refine predictive models, validating outputs to ensure business relevance and model integrity.
- Partner with cross-functional teams to deliver clear data insights through effective visualizations and presentations using Excel, PowerPoint, or similar tools.
- Translate technical results into actionable recommendations, contributing to strategy and operational improvements.
Required Qualifications
- 3–5 years of hands-on experience in data science, analytics, or a related role, preferably in banking, payments, or financial services.
- Proficiency in programming languages such as Python, R, or SQL, and familiarity with tools like SAS or Hadoop is a plus.
- Solid understanding of statistical methods and machine learning algorithms including regression models, decision trees, and clustering techniques.
- Strong communication and presentation skills with the ability to explain technical concepts to non-technical audiences.
- Ability to manage multiple tasks and work effectively in a collaborative, fast-paced environment.
Number of Vacancies
1