Data Scientist - Supply Chain Experience Required - (B3)

About the Job:

We are looking for a Data Scientist to join our Supply Chain Analytics team. The mission of the AGS Operations Business Intelligence team is to enhance efficiency through the application of machine learning, statistical and simulation modeling, and actionable insights.

Our data science modeling and analytical efforts focus on improving process efficiency through insights, enhanced visualization, and improved UI/UX. We aim to elevate our decision support systems and measurement capabilities, driving significant improvements in key business metrics.

Education and Experience:

• Candidates should have 7+ years of experience in a Data Scientist role and a master’s degree in engineering, Operations Research, Computer Science, Statistics, Information Systems, or another quantitative field.
• 5+ years of Supply Chain experience

Key Responsibilities:

• Project Collaboration: Work in project teams as a subject matter expert to design and develop methods, processes, and systems for consolidating and analyzing structured and unstructured, diverse "big data" sources.
• Statistical Analysis: Perform complex statistical and data-mining analysis using tools such as Python libraries (e.g., Pandas, NumPy, SciPy, Scikit-learn), R, SAS, and MATLAB. Responsibilities include the input and design of data acquisition systems, data structure, and database design.
• Customer Interface: Interface with internal customers for requirements analysis and special requests; derive insights and work with business units to determine actions and KPIs for those actions.
• Model Development: Develop complex analytical models, algorithms, and automated processes, applying SQL and Python programming to cleanse, integrate, and evaluate large datasets.
• Collaboration: Collaborate with product and service teams to identify key questions and issues for data analysis and experiments. Facilitate the timely creation of analytical and data science products for the service supply chain by leveraging advanced data analytics, grounded in a strong understanding of business processes and requirements.
• Communication: Communicate insights and findings from analysis and experiments to product, service, and business management to be incorporated into the measurement of effective business processes.

Functional Knowledge:

The ideal candidate should possess a deep understanding of supply chain management and analytics. They should be proficient in using advanced analytical techniques and machine learning models to solve complex supply chain problems. Key areas of expertise include:

• Statistical Analysis and Data Mining: Proficiency in performing complex statistical and data-mining analysis using tools such as Python libraries (e.g., Pandas, NumPy, SciPy, Scikit-learn), R, SAS, and MATLAB.
• Machine Learning: Experience in developing and implementing machine learning models to optimize supply chain processes, clustering, similarity models, causal inference and recommendation engines.
• Data Visualization: Ability to create sophisticated visualizations to communicate insights effectively, using tools like Tableau, Power BI, or Python libraries such as Matplotlib and Seaborn.
• Simulation Modeling: Expertise in building simulation models to improve efficiency and reduce costs in supply chain operations.
• Database Design: Hands-on experience with big data technologies such as Hadoop, Databricks, Apache Spark, Workflows, and Jobs. Excellent SQL and Excel skills are mandatory. Knowledge of data acquisition systems, data structure, and database design to ensure efficient data management and retrieval.
• UI/UX Enhancement: Understanding of user interface and user experience principles to improve the usability and satisfaction of analytical tools and dashboards.

Business Expertise:

• Best Practices: Interpret internal/external business challenges and recommend best practices to improve products, processes, or services.
• Leadership: May lead functional teams or projects with moderate resource requirements, risk, and/or complexity. Demonstrate a high sense of urgency.
• Problem Solving: Lead others to solve complex problems using sophisticated analytical thought to exercise judgment and identify innovative solutions. Knowledge of problem-solving tools (such as 8D, Lean, Six Sigma - DMAIC).
• Impact: Impact the achievement of customer, operational, project, or service objectives; work is guided by functional policies.
• Interpersonal Skills: Communicate difficult concepts and negotiate with others to adopt a different point of view.

Added Advantage:

• Knowledge in Supply Chain Circular Economy - Reverse Value Chain process.
• Published dashboards in Tableau Public with visualization solutions for business problems and earned more views.
• Hands-on experience in Databricks ETL, data ingestion, business intelligence, and AI.
• Hands-on experience in recommendation engines and similarity models.
• Excellent MS Excel skills.
• Experience in causal inference and forecasting techniques.

Qualifications

Education:

Bachelor's Degree

Skills:

Supply Chain

Certifications:

Languages:

Years of Experience:

7 - 10 Years

Work Experience:

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

Yes

U.S. Salary Range:

$142,500.00 - $196,500.00

The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.