As a Data Scientist Lead within the Data and Analytics team, you will spearhead efforts to enhance productivity and efficiency at Chase Bank. You will oversee the impact analysis of improvements to the software development lifecycle from various internal products and programs geared to improving the developer experience.
Job Responsibilities:
- Lead collaboration with product managers, engineers, and other stakeholders to understand business objectives and translate them into data-driven solutions.
- Oversee the analysis of large and complex data sets to identify trends, patterns, and opportunities for improvement in the product development life cycle.
- Direct the development and implementation of predictive models and machine learning algorithms to forecast product performance and operational processes.
- Guide the design and conduct of experiments to test hypotheses and validate model outcomes, ensuring accuracy and reliability.
- Ensure the creation and maintenance of dashboards and reports to visualize key metrics and insights, facilitating informed decision-making across teams.
- Stay up to date with industry trends, emerging technologies, and best practices in data science and analytics.
- Mentor and develop data scientists, fostering a collaborative and innovative team environment.
Required Qualifications, Capabilities, and Skills:
- Bachelor’s degree in data science, Statistics, Computer Science, or a related field.
- Ability to tackle unstructured problems; strong learning aptitude required.
- Experience with data analytics and/or visualization techniques (e.g., SQL, Python, Tableau), as well as data warehousing technologies (e.g., Snowflake, Databricks, Redshift).
- Exceptional communication (written and verbal) and presentation skills – an ability to communicate effectively with diverse audiences across business and technology partners, including senior leadership.
- Proven experience (7+ years) in data science, analytics, or a related role, preferably within the financial services or technology industry.
- Expertise in machine learning techniques, statistical modeling, and data mining.
- Excellent problem-solving skills and the ability to work with complex data sets to derive actionable insights.
Preferred Qualifications, Capabilities, and Skills:
- Experience with Agile methodologies and proficiency in Atlassian tools like Jira and Jira Align to manage workflows and enhance team collaboration.
- Familiarity with analytics engineering tools like dbt and Airflow.
- Familiarity with DevEx metrics and an understanding of software deployment pipelines.
- Familiarity with AI technologies, including prompt engineering and proof-of-concept (POC) development, to leverage advanced analytics and machine learning capabilities.