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Data Scientist/ML Engineer
1 month ago
Job Summary:
As a Data Scientist in the banking domain, you will be responsible for analyzing complex data sets to provide actionable insights that drive strategic decision-making. You will collaborate with cross-functional teams to develop predictive models, enhance risk management strategies, and improve customer segmentation and targeting.
Key Responsibilities:
- Analyze large volumes of structured and unstructured data to identify trends, patterns, and anomalies.
- Develop and implement predictive models to enhance customer acquisition, retention, and risk assessment.
- Collaborate with stakeholders to define business problems and translate them into analytical solutions.
- Create data visualizations and dashboards to communicate findings effectively to non-technical audiences.
- Conduct A/B testing and experimentation to optimize marketing strategies and product offerings.
- Stay updated on industry trends and advancements in data science and banking technologies.
- Work with data engineering teams to ensure data quality and integrity.
Qualifications:
- Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
- 2 to 10 years of experience in data science, preferably within the banking or financial services industry.
- Proficiency in programming languages such as Python, R, or SQL.
- Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn) and statistical analysis tools.
- Strong understanding of data visualization tools (e.g., Tableau, Power BI, or similar).
- Knowledge of banking regulations and compliance standards is a plus.
- Excellent problem-solving skills and the ability to work in a fast-paced environment.
- Strong communication skills, with the ability to present complex data insights to diverse audiences.
