Data Scientist
2 weeks ago
Requirements:
- Minimum of 5 years of professional experience as a Data Scientist, with a focus on machine learning, AI, and data analysis in the banking sector, specifically in mobile banking and internet banking.
- Strong expertise in developing and implementing machine learning algorithms, such as
- Proficiency in programming languages such as Python or R, along with experience working with
- Solid understanding of statistical analysis, experimental design, hypothesis testing, and data visualization techniques. Ability to effectively communicate complex analytical concepts and results to technical and nontechnical stakeholders.
- Experience in working with big data technologies (e.g., Hadoop, Spark) and cloudbased
- Familiarity with data preprocessing techniques, feature engineering, and data quality
- Strong problemsolving skills, with the ability to identify business challenges, frame them into analytical problems, and develop innovative datadriven solutions.
- Excellent communication and collaboration skills, with the ability to work effectively in crossfunctional teams and present findings to stakeholders at various levels of the organization.
- Bachelor's degree in Computer Science, Statistics, Data Science, or a related field. A Master's or Ph.
Responsibilities:
- Develop and implement advanced machine learning and AI algorithms and models to drive insights and solutions for bankingrelated challenges, such as customer segmentation, fraud detection, risk assessment, and personalized recommendations.
- Collaborate with crossfunctional teams, including data engineers, business analysts, and product managers, to identify and define business problems, develop datadriven solutions, and translate them into actionable recommendations.
- Design and build scalable and efficient data pipelines, data preprocessing workflows, and data integration processes to ensure the availability of highquality data for analysis and model development.
- Stay uptodate with the latest advancements in machine learning, AI, big data technologies, and innovative solutions in the banking industry. Evaluate and recommend the adoption of new tools, frameworks, and methodologies to enhance data analysis and predictive modeling capabilities.
- Conduct indepth exploratory data analysis to identify patterns, trends, and anomalies in the data. Communicate findings effectively to stakeholders and provide actionable insights to drive informed decisionmaking.
- Collaborate with stakeholders to define key performance indicators (KPIs) and develop
- Ensure the ethical use of data and maintain compliance with regulatory requirements, data privacy, and security standards within the banking industry.
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