Senior Data Scientist

As a Senior Data Scientist at Rockwell Automation, you will support the development and execution of data-driven solutions that ensure compliance with relevant regulations and policies. This includes gathering, cleaning, and analyzing large datasets from various sources, designing databases for compliance monitoring, and conducting data audits for accuracy. Your role will also involve collaborating with compliance experts to create analytical data models and providing training on compliance data practices.

To qualify for the Senior Data Scientist role at Rockwell Automation, you should have a Bachelor's Degree in Data Science, Statistics, Computer Science, or a related field. Additionally, a legal authorization to work in the U.S. is necessary, as the company does not sponsor work visas for this position. Experience in data analysis, modeling, and reporting, especially in a manufacturing and compliance context, is preferred.

Yes, proficiency in programming languages such as Python, R, or SQL is essential for the Senior Data Scientist position at Rockwell Automation. These skills will enable you to effectively integrate and analyze large datasets, develop algorithms, and automate processes that support compliance and business objectives.

At Rockwell Automation, you can expect a dynamic and inclusive work culture that encourages collaboration and innovation. The company values diverse perspectives and fosters an environment where all team members can thrive. With a hybrid work policy, you will have the flexibility to balance your workload with your personal life, allowing you to be at your best both at work and home.

Rockwell Automation is dedicated to the continuous professional development of its employees, including those in the Senior Data Scientist role. The company provides access to training, resources, and tools that enhance your data science skills and knowledge. They also encourage participation in industry conferences and workshops to keep you up-to-date with the latest trends in data science and compliance.

When preparing large datasets, I focus on several key steps: identifying missing or duplicate data, standardizing formats, and ensuring data integrity. I utilize tools and programming languages like Python and SQL to automate these processes, making it easier to cleanse and prepare the data for analysis efficiently.

In a previous role, I led a project analyzing supply chain data to improve efficiency. I gathered data from multiple sources, developed a predictive model using Python, and analyzed the results to present actionable insights to management. This led to a 20% reduction in inventory costs, demonstrating the value of data-driven decisions.

I have extensive experience using tools like PowerBI and Tableau for data visualization. I leverage these tools to create dynamic dashboards that enable stakeholders to easily interpret data and gain insights quickly. Clear visual representation of findings is critical for driving informed decision-making.

I ensure compliance by incorporating regulatory requirements into my data models from the outset. By collaborating with compliance experts, I design analytical frameworks that meet legal standards and conduct thorough audits to verify that our datasets uphold these requirements.

I have strong proficiency in Python and SQL, which I use for data manipulation, statistical analysis, and automating processes. Python allows me to implement complex algorithms and models, while SQL helps in querying databases to extract the necessary data for analysis efficiently.

One of the most challenging aspects of data science is dealing with unstructured data and ensuring its quality. It requires innovative approaches to transform raw data into a usable format, and this process often involves significant trial and error to achieve accurate results.

In a fast-paced environment, I prioritize tasks based on project deadlines and overall impact on business objectives. I use project management tools to keep track of priorities and communicate regularly with stakeholders to ensure alignment on expectations.

I stay updated by following industry publications, participating in online courses, and attending conferences and webinars. Engaging with the data science community on platforms like LinkedIn also allows me to learn from peers and discover emerging trends and technologies.

Collaboration is crucial since data analysis often involves insights from multiple stakeholders. I engage with teams across functions to gather input and feedback, ensuring that our analysis aligns with business needs and leading to actionable outcomes that drive success.

I want to be a Senior Data Scientist at Rockwell Automation because I admire the company’s commitment to innovation and sustainability. I am excited about the opportunity to leverage my skills in data analysis to contribute to meaningful projects that have a positive impact on industries that serve the global community.