Associate Data Scientist II

Post Holdings Inc.•Brentwood, MO

13d•Hybrid

About The Position

Feeding the world is what we do – how we do it is unique. We are not your textbook consumer packaged goods company. While others may be slow to make change happen, Post continuously drives both inorganic and organic growth. Our history is evidence of that fact with over 100 years of heritage and growth from brands that transcend generations like Honey Bunches of Oats, Fruity Pebbles, Malt-O-Meal, Bob Evans, Kibbles 'n Bits, Egg Beaters, Peter Pan peanut butter and more. Our foodservice and ingredient businesses supply other products you love for brands, restaurants and stores. We have more than 55 offices and manufacturing sites and approximately 13,000 employees. Over the past 13 years, Post has made 28+ acquisitions and innovative financial transactions and reached $8.2 billion in net sales in fiscal 2025. During turbulent times of market uncertainty, the food industry has provided a level of stability unlike other industries Post Holdings, Inc. is a Fortune 500® company headquartered in Brentwood, a suburb of St. Louis, Missouri. Our casual professional atmosphere encourages team members to collaborate, innovate and support our operating companies. Our passion and drive advance the reputation of our operating companies and brands—together, we make a difference. The Associate Data Scientist will primarily focus on data science project execution, using Python, Tableau, Azure ML and SQL to solve challenging problems like forecasting and optimization across all business functions within our portfolio including sales, finance, logistics, operations, IT, and HR. The Associate Data Scientist will be responsible for deployment and support of Machine Learning or AI-enabled software to empower hundreds of decision-makers with the most accurate information about their business and competitive markets. The Associate Data Scientist will help to identify and introduce new cutting-edge technologies to Post’s portfolio.

Requirements

3+ years of experience with collaborative data science or data analytic projects with technical and non-technical stakeholders, driving and communicating tangible business value succinctly.
Bachelor’s degree in Computer Science, Management Information Systems, Economics, Finance, Business, Mathematics, Statistics, or other quantitative subject required, advanced degree preferred
Functional experience in an object-oriented programming language (Python 3.x preferred)
Knowledge of software design (libraries, classes, functions), testing (logging, debugging), and versioning (Git, continuous deployment)
Experience with machine learning platforms and cloud computing, e.g., Microsoft Azure ML (preferred), Amazon SageMaker, Google Vertex AI
Demonstrated expertise in open-source libraries for advanced data analysis, statistical/machine learning models, and optimization, e.g. pandas, sci-kit learn, scipy, and ortools for Python.
Working knowledge or familiarity with business intelligence, reporting, or data visualization software packages (Tableau, PowerBI, Looker, Cognos, R Shiny, D3, Python matplotlib)
Working knowledge in any SQL dialect and knowledge of relational database development in SQL, maintenance, and exception testing experience required (Snowflake, Oracle, or other).
Experience with data modeling strategies, ETL architecture, and related technical documentation, understanding of universe structure types and corresponding functionality, ability to design, execute, and document test scenarios
Advanced user in Microsoft Office Suite, including Excel, Word, PowerPoint & Visio
Knowledge of SDLC/RDLC/DCLC, waterfall, and agile methodologies and practical application when managing or participating in any project, enhancements to database or system configuration, or fulfilling a request for data / reporting
Wide degree of creativity and initiative in problem solving, as well as a drive to streamline / automate / improve and innovate
Excellent written and verbal communication skills, including the ability to concisely convey analytical interpretation and/or data issues to non-technical individuals
Team player mentality that is results driven, customer focused, values learning and innovation
Exhibit trustworthiness, expertise, and the capacity to lead through influence
Self-motivated, strong attention to detail, curious and strong desire to learn

Responsibilities

Contribute to the projects of the data science team, including delivery of high-quality data, self-service, and machine learning and Generative AI solutions, aligning to the overall strategic objectives.
Apply cutting-edge data science tools to enable Post Holdings and its divisions to make better decisions with data.
Consult with marketing, sales, finance, manufacturing, and supply chain teams to understand the highest-value business problems and create data science applications with quantifiable revenue lift or cost avoidance.
Manage machine learning deployments to continually deliver robust, accurate forecasts or recommendations.
Manage small projects where Associate Data Scientist is the only developer.
Consult with internal stakeholders to drive delivering on the scope, success metrics, and delivery timeline.
Develop clear and intuitive data visualizations and dashboards in Tableau, model data with dbt and SQL and present exploratory data analysis results to stakeholders.
Communicate status, priorities and issues with data science leadership, project stakeholders and teammates in a timely manner.
Grow data literacy across the Post Holdings organization to where decisions at all levels are guided by data and analytics.
Summarize and present key results from projects that leverage data science to help solve key business problems.
Contribute to the corporate knowledge of data science and data culture and assist others as they learn data science.
Become an expert on new features within the tool stack (dbt, Tableau, Snowflake and Data Science Python libraries) and share knowledge with others through Post’s training channels.
Drive innovation by keeping abreast of emerging technologies and foster development of the team’s skill base.
Prototype new tools and analysis methods with the intent of growing analytics, machine learning, and data science in every area of the company.
Create documented procedures for configuring, maintaining, upgrading, testing, and coding of analytic applications.
Visualize data in new and innovative ways to drive deeper understanding of the data for technical and non-technical stakeholders.
Partner with data scientists and champion best practices for algorithm development and cloud deployment.
Continuously enhance existing development programs to teach practical applications of data science to young talent and elevate the skills of surrounding team members.