Python Business Analytics Analyst

About this role

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Skills you'll use

What you'll do

• A primary area of focus for this position will be working on threshold tuning for Optimization, developing Logistic Regression Model to predict customer behavior, identifying anomalies in transaction and Customer behavior, Outlier detection, ATL threshold tuning, Segment customers into homogenous groups using clustering, Logistic Regression Model Performance Review etc. while maintaining the flexibility to switch amongst work streams based on business needs. Apply quantitative and qualitative data analysis methods; prepare statistical and non-statistical data exploration and advanced statistical analysis to support the threshold tuning or segmentation work streams.
• Validate data, identify data quality issues (if any), and work with Technology to address them.  Analyze and interpret data reports, draw conclusions and make recommendations answering specific business needs.
• Automate data extraction and data preprocessing tasks. Perform adhoc data analysis. Design and maintain complex data manipulation processes. Provide consistent documentation and presentations.
• Develop new transaction monitoring scenarios based on emerging Financial Crime Risk
• Document solutions and present results in a simple comprehensive way to non-technical audience, as well as write more formal documentation using statistical vocabulary.
• Generate new ideas, concepts and models to improve methods of obtaining and evaluating quantitative and qualitative data. Identify relationships and trends in data, as well as any factors that could affect the results of research. Question and validate assumptions. Escalate identified risks and sensitive areas in terms of methodology and processes.

Who can apply

• 2-4 years of experience in Financial Services / Analytics Industry
• Masters in a numerate subject such as Mathematics, Operational Research, Business Administration, Economics etc. from Premier Institute or a track record of performance that demonstrates this ability.
• Previous experience with financial services companies (retail banking, small business banking, commercial, institutional, private banking)
• Experience in threshold tuning for Optimization, developing Logistic Regression Model to predict customer behavior, identifying anomalies in transaction and Customer behavior, Outlier detection, ATL threshold tuning, Segment customers into homogenous groups using clustering, Logistic Regression Model Performance Review while maintaining the flexibility to switch amongst work streams based on business needs
• Good Knowledge in Python, SQL, Hive
• Experience in prompt Engineering & Generative AI.
• Strong statistics and data analytics academic background and knowledge of quantitative methods
• Highly skilled and good knowledge of MS Excel. VBA experience is a plus
• Experience in reporting the results of analysis in clear written form, and in presenting the findings during meetings and conference calls
• Team working experience (demonstrated team player ability required)

About Citi

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