Grainger, a Fortune 500 industrial supply company, is seeking a talented and driven Senior Applied Machine Learning Scientist to join our expanding data science team. If you are passionate about leveraging cutting-edge machine learning techniques to solve real-world business challenges and are seeking a role with significant impact, this could be the perfect opportunity for you. This role offers a competitive Grainger salary and the chance to work on projects that directly contribute to our mission of keeping the world working.
At Grainger, we are more than just a distributor; we are a vital partner to over 4.5 million customers worldwide, providing essential products, services, and solutions that ensure their operations run smoothly and safely. Our commitment to innovation and customer-centricity drives us to continually seek better ways to serve our clients, and data science is at the heart of this endeavor.
Our Analytics and Data team, comprised of over 50 professionals, is dedicated to transforming data into actionable insights and tangible financial results. As a Senior Applied Machine Learning Scientist, you will play a crucial role in this mission, working collaboratively to develop and deploy machine learning solutions across various facets of our business.
Your Role as a Senior Applied Machine Learning Scientist at Grainger
Reporting to the Senior Manager, Applied Machine Learning, you will be immersed in a dynamic environment where your expertise will be valued and your contributions will be recognized. Whether you prefer the vibrancy of our Chicago, IL or Lake Forest, IL offices or the flexibility of a fully remote setup, Grainger offers a workplace that adapts to your needs.
As a key member of the team, your responsibilities will encompass:
- Problem Solving and Solution Design: You will partner closely with business stakeholders to deeply understand their challenges, identify opportunities for improvement, and translate complex business problems into concrete technical solutions. This involves a consultative approach, working to define the scope and objectives of machine learning projects.
- Collaborative Product Development: Working in tandem with product managers, data engineers, MLOps engineers, and architects, you will contribute to the development of specialized, impactful data products. This collaborative spirit ensures that solutions are not only technically sound but also seamlessly integrated into our business operations.
- Hands-on Data Analysis and Model Building: Your proficiency in SQL and Python will be essential as you delve into large datasets to extract meaningful insights and build robust machine learning models. You will tackle diverse business challenges, including enhancing product recommendations, detecting anomalies, preventing fraud, and optimizing our complex supply chain.
- Data Manipulation and Feature Engineering: You will expertly handle high-volume, high-dimensionality data from diverse sources. This includes visualizing patterns, identifying anomalies and trends, exploring relationships, and performing feature engineering and selection to prepare data for effective model training.
- Scalable Process Development: You will design and implement scalable, efficient, and automated processes for large-scale data analysis, model development, validation, and deployment. This focus on automation ensures the sustainability and efficiency of our machine learning initiatives.
- Model Deployment and API Development: You will be responsible for building, testing, and deploying customer-facing machine learning endpoints and APIs. These critical components will be a blend of business logic, sophisticated models, and rich data, providing real-time insights and capabilities.
- Data Product Visualization: You will create compelling visual representations of data products using open-source web applications. This skill is vital for communicating complex findings in an accessible and impactful manner to business users.
- Business Storytelling and Communication: Effectively communicating complex technical concepts to a wide range of business audiences is paramount. You will excel at “business storytelling,” translating technical details into clear, concise, and actionable insights for both technical and non-technical stakeholders.
- Continuous Product Improvement: You will proactively monitor deployed machine learning products, identifying areas for refinement and implementing continuous improvements to ensure ongoing effectiveness and value generation.
What We Are Looking For in a Senior Applied Machine Learning Scientist
Grainger seeks a highly qualified Senior Applied Machine Learning Scientist with a blend of technical expertise, business acumen, and collaborative spirit. Ideal candidates will possess:
- Educational Foundation: A Master’s degree or Ph.D. in a technical field such as Computer Science, Statistics, Applied Mathematics, Physics, Engineering, or equivalent practical experience. This strong academic foundation underpins your ability to tackle complex analytical challenges.
- Practical Experience: 3+ years of hands-on experience with SQL and Python, with a significant portion of that experience in an analytical role. This experience should include data extraction, in-depth analysis, and the effective communication of findings to diverse audiences.
- Machine Learning Expertise: Proven expertise in building machine learning models using traditional statistical methods. You should be adept at optimizing inference speeds and wrapping models in C/Python code for seamless deployment as REST APIs.
- Cloud Deployment Proficiency: Demonstrated proficiency in deploying machine learning models to cloud environments, utilizing tools such as Docker and Kubernetes. This experience is crucial for creating scalable and robust solutions.
- Data Automation Skills: Experience automating data augmentation and refresh processes using tools like Airflow and Bash Scripting. This skill ensures data pipelines are efficient and up-to-date.
- CI/CD Pipeline Familiarity: Familiarity with CI/CD pipelines for testing and deploying machine learning endpoints. This knowledge is essential for maintaining code quality and ensuring rapid, reliable deployments.
- Endpoint Development Experience: Demonstrated experience in developing and deploying consumable endpoints, including web applications and REST APIs. This experience is key to making machine learning solutions accessible and impactful for end-users.
- Software Engineering Best Practices: Adherence to software engineering practices, including code modularization, testing, and documentation. You should also be proficient in collaboration tools such as Git, Bitbucket, and GitHub for version control and teamwork.
- Exceptional Communication Skills: Strong communication skills, with the ability to clearly and concisely convey complex technical concepts to both technical and non-technical stakeholders. This skill is vital for effective collaboration and impact.
Preferred Qualifications:
- Real-time ML Deployment: Experience deploying machine learning applications in real-time environments.
- Software Engineering Skills: Advanced software engineering skills, including code modularization, testing methodologies, and comprehensive documentation practices.
- Full ML Project Lifecycle Experience: Hands-on experience across the complete lifecycle of a machine learning project, from initial stakeholder collaboration and conceptualization to development, deployment, and continuous monitoring and improvement.
- NLP Expertise: Experience with advanced Natural Language Processing (NLP) techniques.
Grainger Salary and Benefits: Investing in Your Future
The Grainger salary for this Senior Applied Machine Learning Scientist position is competitive and commensurate with experience, qualifications, and geographical location. The expected salary range for this role is between $127,500 – $196,350 annually, with a 10% target bonus. This range serves as a guideline and is not a guarantee of compensation, as final offers are tailored to individual candidate profiles and internal equity considerations.
Beyond the competitive Grainger salary, we offer a comprehensive rewards and benefits package that starts on day one, reflecting our commitment to your safety, health, and wellbeing. Our programs are designed to provide choice and meet the diverse needs of our team members. Benefits include:
- Generous paid time off (PTO) and 6 company holidays per year, ensuring work-life balance.
- Comprehensive health benefits starting on day one, including medical, dental, vision, and life insurance.
- A robust 401(k) plan with a 6% company contribution each pay period, with no personal contribution required, securing your financial future.
- Valuable employee discounts, parental leave options, tuition reimbursement programs, student loan refinancing assistance, and free access to financial counseling and education resources.
Join Grainger and Make a Difference
At Grainger, we are committed to fostering an inclusive and accessible environment where every team member can thrive. We are an equal opportunity employer, proud of our diverse workforce and dedicated to creating a workplace where everyone feels valued and respected.
If you are a passionate and skilled Senior Applied Machine Learning Scientist seeking a challenging and rewarding role with a competitive Grainger salary and exceptional benefits, we encourage you to apply. Come help us keep the world working!
Note: Salary range is indicative and may vary based on experience, qualifications, and location.
