Qualifications:

• Bachelor’s degree or higher in a quantitative field such as Decision Science, Data Science, Mathematics, Statistics, Computer Science, Operations Research, Engineering, Finance, or Economics.
• 5+ years of experience in Financial Services, specifically within cash management, payments, small business, Commercial, or Consumer lending.
• 5+ years of experience solving business problems leveraging data and analytics.
• 5+ years of experience using SQL, R, Python, MatLab, or similar data-mining and analytics applications.
• Skilled in Python, experience with Pandas, Scikit-learn. Experience in machine learning techniques, such as Linear and Logistic Regression, Bayesian models, Decision Trees, Random Forests, Neural Networks, Clustering, Time Series Analysis, Forecasting, Survival / Duration Analysis, or similar. Experience with agile development practices and Git version control.
• Experience with one or more of the DNN frameworks like TensorFlow, PyTorch, etc.,
• Experience with Spark, SQL, Graph stores, or NoSQL stores.
• Domain expertise in financial services, banking, real-time gross settlement and payment related systems Capable of completing descriptive, diagnostic, exploratory, predictive, and prescriptive analytical exercises.
• Proven ability to give meaning, insight, and purpose to information to drive business decisions.
• Capable of managing change through typical strategy development lifecycle stages such as Ideation, Solutioning, Execution, and Go-To Market. Proficient in Excel, Word, and PowerPoint. Excellent communication and presentation skills, problem-solving, time-management, collaboration, and interpersonal skills.
• Proven ability to simply explain complex information to both technical and non-technical audiences.
• Ability to work autonomously as well as in a team setting. Aptitude and willingness to roll-up the sleeves and get involved in the details. Highly curious with the desire to go deep beneath the surface to solve problems.
• Must have good business judgment with demonstrated ability to think creatively and strategically.
• Data science certification or AWS machine learning certification is a plus
• Other Considerations Ability to work in an office environment and to travel to all District offices as needed.
• Ability to perform office duties such as using a computer keyboard. Work involves sitting most of the time but may involve going to other offices and meeting rooms.
• Ability to work in demanding situations and handle multiple priorities Minor lifting and carrying (less than 5 pounds).

Responsibilities:
This position requires a solution-oriented candidate with a combination of deep business acumen, expert knowledge of statistics and algorithm development, and an analytical mindset.
The candidate must have the ability to work with diverse stakeholder groups to solve business problems and provide data solutions that are organized and simple to understand. Become part of this unique opportunity to make history defining the evolution of cloud computing.

Key Responsibilities

• Understands and improves how data is sourced from different sources and ingested with the data integration solution
• Ensures that enterprise architects are addressing all data requirements in their respective projects and solutions
• Perform data manipulation, business analysis, and quantitative modeling to research and design automated solutions
• Closely collaborate with agile delivery , business integration teams & product owners to build data sets based on feature delivery
• Design test cases for systems used for a variety of analytical, transaction processing to ensure the business needs are met and analytics are correctly implemented.
• Analyze application logs, build logs, automation execution logs and defects data to build patterns and predictions using appropriate ML models Provide data analytical expertise and guidance to key stakeholders.
• Identify trends and explain anomalies using data science at scale Develop data structures and pipelines as necessary to support analytical efforts
• Work closely with business integration, performance engineering and product team to build forecast models
• Participate in development/system/database operations as needed (DevOps, sysops, and DBA work) Document parts of the current and future processing framework.
• Build real-time dashboards with help of data visualization tools AWS Quicksight, Tableau or Kibana.
• Use one or more analytical tools from a suite of mathematical/application tools to perform appropriate analysis on specified product, transaction that has multiple variables affecting potential outcomes.
• Perform ad hoc analysis as needed and assist managers of specific functions with analytical, valuation, or pricing projects.
• Collaborate with teams planning or structuring transactions to assist in credit analysis and pricing. Perform other duties as assigned