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Join a team on a data analytics and insights-generation journey, where you’ll help transform how the business accesses data and derives insights. You’ll leverage Databricks and cloud technologies to enhance our data processing capabilities, empower end users to access data swiftly, and unlock insights through AI.
As a Data Scientist-Vice President in Finance Data & Analytics, you will be a pivotal player in developing and optimizing data mining, analytics, and reporting that inform financial trends and strategic initiatives. You’ll build and deploy AI tools and scalable cloud applications, enhance the existing data infrastructure, and partner across finance and MIS teams to ensure data consistency and accuracy. Your work will empower stakeholders to access data quickly and make better, insight-driven decisions.
Job Responsibilities
Partner across finance to develop and optimize data mining and analytics for financial trends and initiatives
Aggregate and mine new and existing data sources to make them available for reporting and analytics
Develop clear, concise reports that identify strategic information and provide performance-improvement recommendations
Lead MIS initiatives and facilitate discussions on impacts and results
Enhance the data available in the existing repository and optimize ongoing data processes
Partner with finance and MIS teams to ensure the consistency and accuracy of data and reporting
Provide analytical and reporting support to the business throughout the month
Drive the development and deployment of AI tools, including building, testing, and reviewing model training
Develop, test, and deploy scalable, efficient cloud applications
Optimize data processing workflows while ensuring data integrity and security
Provide technical guidance to team members and stakeholders, and stay current on cloud technologies and best practices
Required Qualifications, Capabilities, and Skills
5+ years of experience in financial organizations
Bachelor’s degree in Computer Science, Information Technology, or a related field
Experience in SQL database management and development
Expertise in Databricks and cloud platforms such as AWS, Azure, or Google Cloud
Proficiency in programming languages such as Python, Scala, or Java
Experience with data integration, ETL processes, and data warehousing
Familiarity with big data technologies and frameworks
Strong problem-solving, communication, and collaboration skills, with attention to detail
Preferred Qualifications, Capabilities, and Skills
Experience with machine learning and data analytics
Certification in cloud technologies (e.g., AWS Certified Solutions Architect, Azure Data Engineer)
Knowledge of DevOps practices and CI/CD pipelines
Experience with data visualization and analytics tools (e.g., Tableau, ThoughtSpot)
Strong financial and business analytical skills
Ability to work independently and efficiently
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