HP, Inc.

Technology

DataScientist

₹22–35L ~AI est. Chennai, Tamil Nadu, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Data Scientist at HP, Inc.. Skills: Data Science, Machine Learning, Statistical Modeling, Data Visualization. Analyze and interpret complex data sets. Identify trends, patterns, and insights”

What You'll Achieve.

Generate actionable insights and solutions; Create business value and innovation

Industry & Context.

Technology
Problems you'll solve

Analyzing complex data sets; Identifying trends, patterns, and insights; Generating actionable insights and solutions; Resolving project issues; Identifying and recommending improvements

Eligibility Requirements

25% travel

What They're Looking For.

Must Have

Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, Data Science, or any other related discipline or commensurate work experience or demonstrated competence, 7-10 years of work experience, preferably in data analytics, statistical modeling, machine learning, or a related field or an advanced degree with 4-7 years of work experience, SQL proficiency, Python proficiency, R proficiency

Nice to Have

PhD preferred, Specific ML framework experience, Cloud platform certs

What You'll Do.

Analyze and interpret complex data sets

Form business decisions

Improve organizational performance

Consolidate and analyze big data sources

Generate actionable insights and solutions

and automated processes

integrate and evaluate large datasets

Develop predictive and prescriptive models

Define success measures

Track performance of models

Drive implementation of models

Uncover patterns and predictions

Create business value and innovation

Partner with data engineering teams

Create visualizations

Showcase insights and findings

training and mentoring

Collaborate with project team

Communicate project progress

Resolve project issues

Represent the data science team

Identify and recommend improvements

Develop new data sources

Test model assumptions

Fine-tune model parameters

Maintain proficiency within the data science domain

Keep up with technology and trend shifts

How You'll Work.

Team & Collaboration

Data engineering teams; Project team; Data science team

Communication Scope

Technical audiences; Non-technical audiences

Process & Methodology

Project leader

Full Job Description

Data Scientist **Description -** **Job Summary** • This role is responsible for analyzing and interpreting complex data sets using statistical techniques to identify trends, patterns, and insights that can be used to form business decisions and improve organizational performance. The role designs and develops methods, processes, and systems to consolidate and analyze unstructured, diverse big data sources to generate actionable insights and solutions. The role develops programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. **Responsibilities** • Oversees data mining using modern tools and programming languages. • Develops predictive and prescriptive models of moderate complexity to surface insights; drives action, defines success measures and tracks performance of models. • Drives the implementation of models to uncover patterns and predictions creating business value and innovation. • Partners with data engineering teams across multiple business lines to build data pipelines, improve data assets, quality, metrics, and insights. • Creates visualizations and other forms of communication that effectively showcase insights and findings to both technical and non-technical audiences. • Leads a project team of data science professionals and provides guidance, training and mentoring to less experienced staff members. • Collaborates and communicates with project team regarding project progress and issue resolution. • Represents the data science team for all phases of larger and more-complex development projects. • Identifies and recommends improvement upon existing methodologies by developing new data sources, testing model assumptions, and fine-tuning model parameters. • Maintains proficiency within the data science domain by keeping up with technology and trend shifts. ****Education & Experience** Recommended** • Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, D

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