Data Science Intern

Boulder, CO, US, 80302

NetApp

Turn a world of disruption into opportunity with intelligent data infrastructure from NetApp. Realize seamless flexibility—any data, any workload, any environment—with the only enterprise-grade storage service embedded in the world’s biggest...

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Job Summary

NetApp’s Active IQ Artificial Intelligence and Machine Learning power of predictive and prescriptive analytics enables customers and partners to automate data center operations and achieve extremely low total cost of ownership and avoid issues before they become a reality. Today, 98% of technical issues with NetApp products are automatically identified by Active IQ with prescriptive steps to avoid the issue – and we simply want to do better and more. Every day, one-half million active IOT end points feed the Active IQ multi-petabyte data lake with structured and unstructured data. That’s the pool you will have at your fingertips to continue to enhance NetApp’s world class data visionary analytic capabilities.


As an intern on the Active IQ Data Science team, you will analyze customer meta-data and build high-end analytical models for solving high-value business problems, such as storage and IT ecosystem durability and health, network robustness, and enabling always on always available storage ecosystems.


At NetApp, our products and solutions enable customers to unleash the power of their data. In the Active IQ team, we unleash the power of our own data at NetApp.

 

Responsibilities:

  • Processing and analyzing large volumes of data.
  • Building predictive models with advanced machine learning algorithms such as Neural Networks, Decision Trees, Boosting/Ensemble methods, Clustering, etc.
  • Implementing data quality checks to ensure that all reporting and modeling is using correctly sourced data.
  • Interacting with business teams from the data analysis stage to the final report presentation.
  • Assisting Product Managers as needed to define and refine business use cases.
  • Writing coherent reports and making presentations on high-end analytical projects.
  • Communicating verbally and in writing with peer technical team members as well as business leaders.
     

Job Requirements

Essential Requirements:

  • Working towards a Bachelor’s or Master’s degree in Data Science & Statistics / Mathematics or related field
  • Experience in Machine Learning, Scripting, and Statistical & Reporting tools (Python, R, SQL, etc.).
  • Knowledge of at least some supervised and unsupervised modeling techniques such as Logistic/Linear Regression, SVMs, Neural Networks / Deep Networks, Boosting/Ensemble methods, Decision Trees, Clustering, etc.
  • Willingness to extend beyond core data science work to perform -data wrangling, data prep and data transfers, data quality checks, deployment, monitoring
  • Ability to communicate clearly across data science team members
  • Experience with SQL and relational databases
  • Experience with unstructured and semi-structured data sources and requisite processing tools.
     

Additional Skills and Abilities:

  • Excellent written and verbal communication skills.
  • Ability to think analytically, write and edit technical material, and relate statistical concepts and applications to technical and business users.
  • Ability to work both independently and in a team environment.
     

Preferences:

  • Experience in mathematical/statistical modeling, pattern recognition, or data mining/data analysis.
  • Experience specifying, building, and maintaining advanced analytic solutions with large-scale transaction data.
  • Experience working in a team to perform data management, deployment and product support for advanced analytic solutions.
  • Experience building solutions that leverage Large Language Models.
  • Ability to translate model performance to benefit for the business by incorporating knowledge of business owner practices and needs.
     

Education

Must be enrolled in an educational or professional program through summer 2025 or later.  

Compensation:
Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off (PTO), various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU’s), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. 

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Tags: Clustering Data analysis Data management Data Mining Data quality LLMs Machine Learning Mathematics Python R RDBMS SQL Statistical modeling Statistics Unstructured data

Perks/benefits: Career development Competitive pay Equity / stock options Health care

Region: North America
Country: United States

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