Data Scientist - Hybrid Analytics & Modeling

Hewlett Packard Enterprise; Houston (TX); Hybrid; USD 109,000 - 251,000; Full time

Benefits offered by this job

Health & wellbeing

Personal & Professional Development

Unconditional Inclusion

Job summary

Hewlett Packard Enterprise in Houston, TX is seeking a Data Scientist for a hybrid schedule (average 2 days in office). You will design and apply advanced analytics to turn structured and unstructured data into practical, business-ready insights and help embed analytics into operational processes and applications.

The role requires 2+ years of experience, a degree in Statistics/Operations Research/Computer Science (Master’s preferred), and strong knowledge of regression, neural nets, CHAID,

Qualifications

• Bachelor-level/ master preferred in a quantitative field.
• Experience applying analytics to business problems.
• Proficient in Python, SQL, R, SAS and visualization tools.

Responsibilities

• Formulate analytics objectives and technical requirements based on user needs and business processes.
• Conceptualize, build, develop, and enhance client analytic models.
• Select modeling methodologies considering data availability, cost, and timing constraints to deliver insights.
• Embed analytic models into operational processes by collaborating with Application Developers.
• Measure business performance based on the model.
• Lead model enhancements and communicate insights with visual models to simplify the user experience.

Skills

Python

SQL

R

SAS

Java

Unix Shell

Machine Learning

Data Visualization

Communication

Education

Bachelor's in Statistics, Operations Research, Computer Science

Master's degree preferred

Tools

Informatica

Ab Initio

Talend

Spotfire

Tableau

Hadoop

HTML5

D3

SAS

Python

SQL

Unix Shell

Job description

Hewlett Packard Enterprise in Houston, TX is seeking a Data Scientist for a hybrid schedule (average 2 days in office). You will design and apply advanced analytics to turn structured and unstructured data into practical, business-ready insights and help embed analytics into operational processes and applications.

The role requires 2+ years of experience, a degree in Statistics/Operations Research/Computer Science (Master’s preferred), and strong knowledge of regression, neural nets, CHAID,