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:

• PGP or Masters in Data Science / Advanced Analytics / AIML
• 3+ years of experience working in Large Banks/ Financial Services.
• Good in SQL, Python for data analysis and usage of libraries. 
• Good written and oral communication skills, and interpersonal skills.