In this role, you will:

• Participate in low to moderately complex initiatives by utilizing data-driven, advanced analytical and statistical techniques to identify trends, diagnose problems, and build actionable insights or recommendations

• Review and analyze business, operational, technical assignments, or challenges that require research, evaluation, and selection of alternatives to convert data into meaningful insights and recommendations

• Exercise independent judgment to guide medium risk business hypothesis generation

• Present recommendations and insights for resolving low to moderately complex business needs and problems; exercise independent judgment while developing an expertise in analytic capabilities

• Collaborate and consult with functional colleagues, internal partners, and stakeholders to drive recommendations and strategies based on data-driven analytical insights, trends, and patterns

• Conduct low to moderately complex predictive analytics to build actionable insights and recommendations

• Design and apply algorithms to mine large sets of structured and unstructured data from various sources

• Ensure data completeness, accuracy, and uniformity through cleaning and validation

• Interpret and analyze data, using advanced analytics modeling methods and programming, to isolate patterns that lead to recommendations to solve problems and influence business decisions and strategies

Required Qualifications:

• 2+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications:

• Good in SQL, Python, PySpark for data analysis and usage of libraries.

• This role is for a Data Science Consultant within the CDAI (Consumer Data, Analytics and Artificial Intelligence) function. 

• We are seeking highly skilled and talented individual who will form part of an agile group of professionals that will work across the Consumer, Small & Business Banking (CSBB) core businesses and functions to provide deep analysis and strategic solutions to enable existing and new businesses to develop and expand.

• Specifically, we are looking for someone with an analytical acumen and ability to define hypothesis & assumptions, lay out data requirement, gather, and analyze data and apply the business P&L (revenue, cost, margin, etc.) levers to derive insights and refine strategies.

• The work will involve identifying areas for opportunities and growth within each initiative leveraging analytical thinking & rigor to ensure that it correlates back to the overall strategy of the CSBB and the broader enterprise

• This role is for our Customer Analytics team, and you will be responsible to analyze and transform customer data into actionable insights for enhanced engagement and experience. Leveraging advanced analytics to drive strategic decision making and empowering businesses to cultivate lasting relationships to drive growth through a deep understanding of customer behavior across Lines of Business (LOBs).

• Data Analytics, Insight Generation and/or Data Science  

• Experience working in Large Banks/ Financial Services to translate business problems into actionable insights, with demonstratable experience of delivering strategic insights and recommendations.

• Bachelor's degree or higher in a quantitative field such as applied math, statistics, engineering, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis  

• Experience in data analysis, data extraction/manipulation and loading routines using SQL, Teradata, database structures and data warehouses.  

• Effective communication skillset: ability to convey results, concepts, and issues/challenges with us and partners / peers and non-technical marketing/business audience through executive ready presentations.

• Experience with statistics and basic statistical modeling techniques (i.e., regression, decision tree, random forest, clustering, segmentation etc.)    

• Good Story telling competencies to create new and novel analytics approach or data visualizations to deliver Insights to target audience.  

• Self-motivated to identify opportunities and propose solutions to business partners.

• Languages: SQL, Python, SAS/R, PySpark

• BI Tools: Tableau/ Power BI/ Excel

• Good knowledge of building strategic analysis using customer profiling, business segmentation, heuristics, inferential statistics, RFM analysis

• Experience of working with Machine learning techniques – Segmentation, Regression, Decision Trees, Forecasting, Clustering

• Financial services experience

• Good written and oral communication skills, and interpersonal skills.