Manager of Data Science

The Manager of Data Science role is organizationally under Finance & Accounting, within the Decision Support tower. Particularly, this role will report into the Business Intelligence & Advanced Analytics space. The Manager of Data Science is responsible for leveraging big data sets to drive predictive and prescriptive insights in various areas of UPS business. He/she should assess and scope business needs, conduct research, and design/develop integrated solutions to a variety of business problems.

This role is hybrid, with the expectation to have in-office presence 3 days per week.

Scope and responsibilities of the role include, but not limited to:

• Use various analytical methods such as predictive modeling, text mining, machine learning, statistical forecasting, optimization, and simulations to develop and implement advanced statistical and econometric decision support systems.
• Successful candidate will work with a team that is responsible for researching and implementing advanced analytics models utilizing a diverse set of techniques.
• This individual will perform data wrangling, ETL, and data exploration tasks, while leveraging large volumes of structured and unstructured data.
• Design and leverage various types of customer segmentation models to identify opportunity for growth and assess overall customer health. Integrate performance and impact within revenue and drive coordination between Marketing, Sales and Operational initiatives

Project Management 

• Manage projects across the lifecycle, working with cross functional teams consisting of data scientists, data engineers, application developers, business analysts and various stakeholders. Manage the execution of analytics projects based on statistics, machine learning, experimental design, and the scientific method principles to derive insights.

Thought Leadership

• He/she should be a natural thought leader, thinking outside of the box, and challenging the status quo.

Upskilling Peers and Team 

• Manage and develop analytics peers and other data science focused team members; have an active role in the Citizen Data Science program

Collaboration

• Work with various department project teams and facilitates collaboration with cross-functional stakeholders. Collaborate with various groups to gather, curate, and build data sets needed to successfully construct the foundation of our Analytical Models. Collectively develop hypotheses, approaches, models, and solutions to solve problems and increase profitability and efficiency.

Data Visualization

• Leverage analytics and visualization tools to design and present information to drive fact-based decision making

Continuous Learning

• Develop subject matter expertise on internal and external sources of information. Stay up to date with the industry trend to gain knowledge of latest hardware and software, emerging technologies, and analytic techniques to ensure UPS is utilizing state-of-the-art tools. This candidate would be encouraged to network and learn about best practices and emerging technologies.

Preferred Qualifications

• Master's Degree with 5+ years of data science/advanced analytics experience or a Ph.D. with 2+ years of advanced analytics experience (Degree in Operational Research, Mathematics, Engineering, Statistics, Economics, Data Science, Computer Science, Data Analytics or related field)
• The ideal candidate should have a healthy level of curiosity, be a strong communicator, and possess the ability to tell the story of data results and insights.
• Fluid understanding of economics, with a solid foundation in statistics, ability to seek and solve quantitative problems through data modeling.
• Preferred Expertise with statistical languages such as R and/or Python Strong understanding of statistics and probability: distributions, experimental design, variance analysis, A/B testing, probability theory, stochastic systems, and Bayesian inference Expertise with various statistical modeling algorithms such as: regression, clustering, ARIMA, decision trees, Time Series, and scenario simulation/modeling.
• Expertise in machine learning algorithms and experience using the following ML techniques: Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Clustering and Neural Networks Working experience with database systems (e.g. SQL, NoSQL, Teradata, MongoDB, Postgres, etc.)
• Must have expertise with statistical languages such as R and/or Python Must have a strong understanding of statistics and probability: distributions, experimental design, variance analysis, A/B testing, probability theory, stochastic systems, and Bayesian inference
• Must have expertise with various statistical modeling algorithms such as: regression, clustering, ARIMA, decision trees, Time Series, and simulation
• Master's Degree with 3+ years of data science/advanced analytics experience (Degree in Business, Computer Science, Data Analytics, or similar focus). Otherwise, must be a current UPS employee with three years of data science and analytics centric UPS experience.

• Experience with Big Data technologies like Hadoop, Spark, Hive, NoSQL, etc., and Cloud technologies (Google Cloud, SQL Server, Azure, etc.)
• Strong analytical and problem solving skills.
• Advanced skills to work with large, complex, and disparate data (accessing, connecting, and analyzing data), using tools such as Snowflake, Alteryx, or similar applications.
• Data visualization and dashboard development experience, with tools such as Tableau, Power BI, or similar applications.