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Job Summary
Looking for experts that can leverage agile processes on a wide range of business and product-focused analytics projects!
As a Data Scientist Senior Associate, within the Machine Learning and Intelligent Operations team, you will support advanced analytics projects across various Operations functions, channels, and products to support Machine Learning and AI initiatives across Consumer Banking and lead initiatives focused on improving Agent AI assistant.
Job Responsibilities
- Conduct in-depth data analysis to extract actionable insights, identify trends, and support data-driven decision-making across various servicing and operations functions, while focusing on improving customer and agent experience while reducing operating expenses for the Consumer Banking Operations space.
- Apply advanced statistical techniques and gained business knowledge to improve efficiency, reduce costs, and enhance the performance of operations.
- Work closely with cross-functional teams across engineering, design, and product to ensure the successful rollout of ML/AI solutions into business processes and systems and utilize enterprise data to develop automated data solutions using a mix of customer, account, digital, telephony, financial, and operational data.
- Oversee data collection, cleaning, and preprocessing to ensure high-quality input for machine learning models and analytics projects.
- Develop and deliver clear, concise reports and visualizations to communicate findings and recommendations to stakeholders, including senior management.
- Stay abreast of the latest developments in machine learning, artificial intelligence, and data analytics, and apply innovative techniques to enhance the bank's analytics capabilities.
- Leverage the agile process to deliver a wide range of business and product-focused analytics, including building and updating business cases, exploratory analysis to identify product enhancement opportunities, generating feature performance metrics and dashboards, and crafting data stories and presentations of key findings to stakeholders.
Required Qualifications, Capabilities, And Skills
- 3+ years of related experience with a Bachelor's degree in a quantitative or related field.
- Experience delivering analytics solutions following an Agile (Scrum or Kanban) methodology.
- Hands-on experience with standard data analytics tools and technologies (SQL, R, Python, Tableau, Alteryx, Snowflake, SAS).
- Familiarity with AWS, data mining, statistical modeling, machine learning, and other advanced analytics methods.
- Hands-on experience writing code and automating processes to source, transform, and analyze data from multiple sources, including structured and unstructured data.
Preferred Qualifications, Capabilities, And Skills
- Graduate degree in a related field is preferred.