Data Scientist

At Applied Materials, we are building the next generation fab automayion solutions using Artificial Intelligence and Machine Learning. Our AI/ML team is looking for a Data Scientist who will be responsible for building predictive and prescriptive models to increase and optimize fab productivity. The data scientist must be self-directed and independent in conducting their work as well as working with and supporting globally distributed teams. The right candidate will be excited by the prospect of building our company’s next generation data science practice and products.

Responsibilities

• Formulate and lead guided, multifaceted analytic studies against large volumes of data.
• Interpret and analyze data using exploratory mathematic and statistical techniques based on the scientific method.
• Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.
• Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.
• Develop, productize and maintain machine learning and optimization models according to requirements to transform our product into an innovative industry leader
• Analyze problems and determines root causes.
• Work with stakeholders including the Product management, Data and Design teams to build models.
• Support our customers with their data science and optimization problems using our product

Qualifications

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience working with ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres, Cassandra, MongoDB.
• Experience with cloud AI services from AWS, Google, Azure
• Experience with optimization tools: Gurobi, CPLEX, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Education/Experience

• Candidate with 7+ years of experience in a Data Scientist role, who has attained a Graduate degree in Operations Research, Computer Science, Statistics, Informatics, Information Systems or another quantitative field.

Qualifications

Education:

Bachelor's Degree

Skills:

Certifications:

Languages:

Years of Experience:

4 - 7 Years

Work Experience:

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

No

U.S. Salary Range:

$132,000.00 - $181,500.00

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.