Sr. Data Analyst, Supply Chain Analytics

## Sr. Data Analyst, Supply Chain Analytics Apply locations:
Ohio - Fieldtime type:
Full time posted on:
Posted Yesterday job requisition :
R25627

Here at Scotts Miracle-Gro there is no such thing as a typical day. Our culture is constantly energized by new and exciting growth opportunities and at a rapid pace. Below are details on an open job. If the role interests you and you would like to be considered we encourage you to apply!

As a
** Senior Data Analyst
** in our Supply Chain Analytics group you will play a critical role in analyzing complex data, creating insights and predictions, and automating analytical processes.

Your goal is to produce and deploy predictive analytics that help the Scotts Miracle-Gro Supply Chain anticipate the future and make better, faster decisions. You will collect and build datasets from multiple sources, use statistics to understand the data, and turn the resulting analytics into sustainable workflows that power our decision-making, planning, and forecasting. You will also help business users work more efficiently by providing them with better data, resolving data bottlenecks, and automating the analytics they need to drive our company towards our financial goals.

The position requires advanced analytical skills, complete comfort working with large datasets, passion for continuous improvement, and collaboration with cross-functional teams. Good communication skills are as essential as good analytic skills.

This is your opportunity to drive
*** transformative
* ** change and make a difference in vital business decisions, while working with best-in-class technologies and growing your skills. If this is your calling, then here is what you can expect to do in the role:
** Data Analysis and Interpretation**:
Conduct in-depth analysis of large, complex datasets that encompass Sales, Marketing, and Operational data to derive meaningful insights for the future. Interpret data trends and patterns, providing actionable recommendations to stakeholders. Leverage the right Python libraries, SQL, or other tools for the job.
** Building, Cleaning, and Maintaining Large Datasets**:
Combine data from various sources (from local text and Excel files to SQL tables and data lakes). Clean and process raw data to create large, actionable datasets that can be analyzed or used in various workflows. Select the right tools for each task. Take ownership of the quality of the resulting data.
** Automating Analytical Workflows**:
Create automated pipelines to extract, process, and analyze data. Turn ad hoc analyses and predictive models into sustainable, self-contained processes.
** Predictive Analytics and Modeling**:
Utilize advanced statistical techniques to establish causal relationships and generate accurate forecasts of how business variables will affect future sales
** Report Development and Visualization**:
Design, deploy, and maintain comprehensive reports and dashboards using BI tools in collaboration with our BI team (e.g., Tableau, Looker).
** Stakeholder Collaboration**:
Collaborate with business stakeholders to understand their information needs. Gather requirements for analytical projects and create a plan of action to deliver the right data in the right way. Present findings and insights to both technical and non-technical audiences.
** What you’ll need to be successful:*
* -Bachelor's or Master’s Degree:
Data Analytics, Data Science,  Information Systems, or Statistics (a degree in a different field will be considered if candidate has substantial work experience with predictive data analytics and coding)-2 - 3 years of experience with data analytics in Python and SQL  
-2 - 3 years of experience working with cross-functional teams in a corporate environment

Demonstrated experience delivering large scale analytical projects (from raw data to fully deployed models and reports) in a corporate environment
** Key

Skills:

*
* -Python   
-SQL  
-Strong knowledge of core Python libraries, Pandas, and Numpy  
-Cleaning, combining, and preparing a wide variety of data formats for analysis, including messy data with missing values, problematic data types, etc.  
-Handling very large amounts of data (millions…