Data Science Intern

Quick Facts

This requisition may be classified as on desk or hybrid depending on location and role. Hybrid requires working on average 2 days per week from an HPE office.

Description

This internship contributes to data science work transforming structured and unstructured data into actionable insights. The role focuses on analyzing and validating data, preparing datasets for EDA/hypotheses, supporting metadata and hypothesis matrix development, building and validating models, and visualizing model insights and analytics user experience/configuration tools.

Responsibilities

• Participates in the analysis and validation of data sets/solutions/user experience.
• Aids in the development, enhancement and maintenance of a client's metadata based on analytic objectives.
• May load data into the infrastructure and contributes to the creation of the hypothesis matrix.
• Prepares a portion of the data for the Exploratory Data Analysis (EDA) / hypotheses.
• Contributes to building models for the overall solution, validates results and performance.
• Contributes to the selection of the model that supports the overall solution.
• Supports the research, identification and delivery of data science solutions to problems.
• Supports visualization of the model's insights, user experience and configuration tools for the analytics model.

Requirements

• Working towards a Bachelor's and/or Master's degree with a focus in Data Science, Computer Science, Computer Engineering, Software development, or other IT related field.
• Basic knowledge of data science methodologies.
• Basic understanding of business requirements and data science objectives.
• Basic data mapping, data transfer and data migration skills.
• Basic understanding of analytics software: R, SAS, SPSS, Python.
• Basic knowledge of machine learning, data integration, modeling, and ETL tools: Informatica, Ab Initio, Talend.
• Basic communication and presentation skills.
• Basic data knowledge of relevant data programming languages.
• Basic knowledge of data visualization techniques.

Benefits

• Health & Wellbeing: comprehensive suite of benefits supporting physical, financial and emotional wellbeing.
• Personal & Professional Development: programs to help reach career goals; options to become a knowledge expert or apply skills to another division.
• Unconditional Inclusion: flexible work/life management and emphasis on individual uniqueness.