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Title:  Senior Data Science


Sunnyvale, CA, US, 94089

Requisition ID:  25536

Job Summary

Job Summary


NetApp is looking for a Data Scientist focused on providing data-driven, action-oriented solutions to challenging business problems. Business-minded data scientist with a demonstrated ability to deliver valuable insight via data analytics and advanced data-driven methods. Relied on as a key advisor in driving global growth. The ideal candidate is an independent, solution-oriented thinker with a strong background processing large data sets, applying analytical rigor and statistical methods, and driving towards actionable insights and novel solutions. Forward-thinking business skills that enable collaboration and data mining with varied business units

Specific Responsibilities

  • Accountable for translating complex analytical concepts into actionable results
  • Develop predictive data models that will help to personalize interaction with business
  • Analyze and process complex data sets using advanced querying, visualization and analytic tools
  • Produce appropriate and effective project deliverables
  • Identify, measure and recommend improvement strategies for KPIs across all business areas
  • Product appropriate and effective project deliverables
  • Demonstrate a strong understanding of project scope, data extraction methodology, design of dependent and profile variables, logic and design of data cleaning, exploratory data analysis and statistical methods
  • Demonstrate the ability to analyze, design, develop and implement solutions that increase customer value and embrace simplicity, speed, adaptability, and sustainability 
  • Work closely with Information Architect and business teams to understand the data from end to end perspective across business domains enterprise wide
  • Partner with the Data Architect to build the optimal advance tools and self-service capabilities for the business units
  • Build a Data Science and Analytics Center of Excellence across the enterprise
  • Evangelize the need for Data Science practice and drive key strategic conversations/programs with Data

 Day to Day

Define requirements for new enterprise statistical solutions and hand off requirements documents to Data Architect for the team to deliver

Developing machine learning, optimization, or other modeling solutions as required

Design and develop reports/dashboards by interpreting the business, user, functional, and non-functional requirements

Produce appropriate and effective project deliverables on problems such as, sample diagnostics, customer profiles, complex queries, data mining, model algorithms, charts, model score distributions, etc

Development and execution of all analytical data sets and statistical analysis relating to projects

Find insights in large and fragmented data sets across database types and tools

Work with multi-disciplined team taking full ownership of turning discoveries and ideas into models

Drive CoE across the enterprise by collaborating with various IT, Business stakeholders and Data Science community

Engage in major projects and programs to validate the business problems or identify new opportunities within a project through Data analysis


  • Contribute to development of methodologies and processes for the team
  • Able to communicate with all levels of management
  • Effectively communicate with internal and external stakeholders to develop requirements
  • Build a Data science COE spanning across business and IT domains



Job Requirements

The requirements listed below are representative of the knowledge, skill, and/or ability required to be a successful Data Scientist at NetApp.

  • Ability to apply data science and data characterization technologies.
  • Must work across diverse projects in a dynamic and collaborative environment.
  • Conduct end to end analysis and apply novel solutions from the best of academia, open source, and commercial against our most challenging problems.
  • Assess and discover technology developments, determine relevance to projects, and operationally prototype them against real world data and problems in actual code using agile development techniques.
  • Interact cross-functionally with a wide variety of people and identify opportunities to incorporate advanced analytics into existing workflows.
  • Communication is a key skill; The ability to match technologies to business objectives and explain it in layman’s terms is mandatory
  • Must be current on technologies and systems and be able to explain them to audiences of all levels and functions
  • Must be organized and analytical, adept at working in a team environment, able to design and implement a project schedule, and able to handle multiple priorities 
  • Must have High tech industry experience in at least one of the business domains (Idea to Offer, Offer to Quote, Quote to Invoice, Forecast to Delivery, Financial Management, Install to Support)


Experience with the following required:

  • Broad understanding of statistical theory and application
    • Statistical tools (R, R Studio, tidyverse, SQL Server R Services)
    • ETL development skills. Advanced T-SQL to support data collection, cleaning and validation.
    • Advanced visualization training tools: Tableau, MS Power BI and others as they become available
  • Experience with state-of-the-art techniques in machine learning algorithms, including deep neural networks, NLP, kernel methods, dimensionality reduction in supervised and unsupervised contexts, ensemble methods, network analysis. 
  • Strong analytical and data processing skills and comfortable working with large data sets and ability to transform data into actionable insights.
  • Exceptional technical skills:
    • Strong programming skills in at least one language such as Python, Java, Scala, C++, Julia
    • Experience with SQL and relational databases.
    • Experience with unstructured & semi-structured data sources and requisite processing tools.
  • Ability to work in an agile environment.
  • Experience using Hadoop, MapReduce, Spark and/or other distributed processing tools.


Education and/or Experience

  • Graduate degree in Mathematics, Statistics, Computer Science, Data Science or a closely related education with 10+ years of experience in IT industry with a focus on Statistics or Analytics
  • Experience with common methods used in regression and classification problems (e.g. Random Forests, Support Vector Machines, etc.) 
  • Experience with Time Series Analysis, Survival Analysis, fixed and random effects, and developing models in contexts where observations are not IID

Knowledge and experience with advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, experimental design, and proper usage, etc.)

Nearest Major Market: San Jose
Nearest Secondary Market: Palo Alto

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