Workforce Insights Specialist - Data Science

Caterpillar Inc.•Nashville, TN

1d•$97,530 - $158,480•Onsite

About The Position

Caterpillar uses analytics to identify and create opportunities for the workforce to deliver on our business priorities. Some typical opportunities include identifying markets and segments with key skills and talent to execute on businesses priorities, modeling scenarios and risks to our current and future talent, evaluate the effectiveness of operations and strategic initiatives, and recommend key areas to influence outcomes with data and insights. Our global team will provide analytical thought leadership for COEs, Segments, and Functional solutions and initiatives. The principal responsibility of Workforce Insights Specialist is to provide a unique combination of statistical expertise, critical thinking, business acumen, inquisitiveness and creativity to deliver workforce solutions and insights across the enterprise. In addition, they will continue to elevate thinking amongst the analytics team, COPs, and all its partners to grow the analytical capabilities across all HR. Some challenges of this role include working with Segments and COEs that may have conflicting priorities; shifting paradigms and thinking regarding data and analytics; balancing the need for precision vs minimally viable solutions; scaling the significant demand for data and analytics to focus on value added activities. The Workforce Insights Specialist will elevate the rest of the team by establishing sound analytic approaches addressing business challenges across the enterprise. The role reports into a Global Analytics Lead that is responsible for helping build a data driven culture and create analytical solutions that improve decision making and reveal new opportunities. They must demonstrate good communication skills to explain conclusions to customers and leaders across all levels of the organization.

Requirements

Possess knowledge of business concepts, tools, and processes that are needed for making sound decisions in the context of the company's business; ability to apply this knowledge appropriately to various situations.
Business Statistics: Knowledge of statistical methods, analytical techniques, and data interpretation practices used to identify business needs, uncover opportunities, detect trends, and support data-driven decision-making through analysis.
Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.
Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
Machine Learning & Artificial Intelligence: Understanding of machine learning and artificial intelligence technologies and their application in data analysis; ability to use AI-driven approaches to interpret data, recognize patterns, and support evidence-based decision-making.
Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.

Nice To Haves

Bachelor’s degree, preferably in statistics, economics, mathematics, or a similar field
Experience working with Snowflake and AWS highly preferred
Knowledge of programming languages with R preferred followed by Python
Experience working with BI tools such as Power BI and Tableau.
Strong consultative skills, initiative, and the ability to communicate and tell compelling stories with data.
Ability to utilize AI responsibly to streamline and enhance analytics approaches to solve workforce challenges.

Responsibilities

Provide a unique combination of statistical expertise, critical thinking, business acumen, inquisitiveness and creativity to deliver workforce solutions and insights across the enterprise.
Elevate the rest of the team by establishing sound analytic approaches addressing business challenges across the enterprise.
Oversee the acquisition and consumption of data from structured and unstructured sources, while ensuring quality and comprehensiveness of data for use in analyzing business activities, detecting patterns, and communicating trends.
Demonstrate an ability to utilize various methods and techniques, including AI, to frame opportunities and conduct analyses that result in productive decisions.
Develop predictive data models, quantitative analyses, and implement semantic data capabilities utilizing machine learning techniques.
Lead data exploration and analytics projects and provide on-going coaching regarding visualizations, data mining, and analytic techniques.
Demonstrate an ability to tell a story with data and create compelling ways to use data to drive actions.