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Mid-level analytics role in a metro with broad Python/SQL and BI requirements increases applicant competition.
Core analytics and modelling skills transfer across industries, but financial-services context raises sensitivity.
Explicit 3–5 years plus mandatory SQL, Python and BI skills make shortlisting relatively strict.
Translate business questions into hypotheses and perform advanced analytics to identify trends, risks, and business drivers across customer, commercial, and operational data.
Develop, test, validate, and support operationalization of statistical and machine-learning models using Python or equivalent tools.
Define requirements and KPIs for dashboards and analytical products, partner with developers for reporting solutions, and automate analysis to improve efficiency.
Bachelor's or Master's degree in Analytics, Statistics, Economics, Mathematics, Computer Science, Engineering, Business or related field, or equivalent practical experience.
3–5 years of experience in analytics, data science, customer analytics, or related roles.
Strong SQL skills and proficiency in Python or R for data analysis, plus experience with data visualization tools like Power BI or Tableau.
Work Experience Required: Approximately 3–5 years in analytics or related analytical role.
Experienced in working with complex datasets to generate actionable business insights and communicate findings to technical and non-technical stakeholders.
Proficient in model development, evaluation, and operationalization, with knowledge of machine-learning techniques and statistical concepts.
Collaborative in cross-functional Agile teams, capable of partnering with business stakeholders and technology teams to deliver analytics solutions.