Data Science Technical Lead/Manager Job - Lewisville, United States - PACCAR

Description

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Data Science Technical Lead/Manager Job


Date:
Oct 31, 2023


Location:
Lewisville, TX, US, 75067

Company:

PACCAR
Company Information


PACCAR is a Fortune 500 company established in 1905.
PACCAR Inc.

is recognized as a global leader in commercial vehicle, financial, and customer service with internationally recognized brands such as Kenworth, Peterbilt, and DAF trucks.

PACCAR is a global technology leader in the design, manufacture, and customer support of premium light-, medium- and heavy-duty trucks under the Kenworth, Peterbilt, and DAF nameplates and also provides customized financial services, information technology, and truck parts related to its principal business.

Whether you want to design the transportation technology of tomorrow, support the staff functions of a dynamic, international leader, or build our excellent products and services, you can develop the career you desire with
PACCAR.

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PACCAR Powertrain Summary

For nearly 125 years,
PACCAR has been on the leading edge of commercial transportation technology.

PACCAR Powertrain is the newest business unit formed to take the industry in a direction meeting the needs of the 21st century.

From axles and transmissions to low-emission diesel to alternative fuels, to hydrogen technologies and battery electric power,
PACCAR Powertrain is leading the industry through this century and into a cleaner, greener, and more power-efficient future.

Job Functions / Responsibilities

Lead data science team by building a culture of creative problem-solving, and innovative solutions.
Provide a mentorship atmosphere to help the team of data scientists grow technically, and professionally.

Conduct end-to-end analyses to solve business problems including, but not limited to, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
Build and operationalize data pipelines, analytical tools, and decision support models
Creatively identify and pursue predictive analytics opportunities to solve business problems and drive value
Define and evaluate key metrics and understand what moves them and why
Strategize on making analyses easily repeatable, accessible, and actionable
Proactively identify and develop expertise in new technologies, methodologies, and advanced statistical techniques
Communicating technical ideas to non-technical stakeholders by translating complex findings and results into a compelling narrative
Qualifications

5 years of data science experience and tech industry experience
3 years of leadership experience
Applied experience with machine learning on large data sets and advanced statistical techniques
Experience articulating business questions and using mathematical techniques to arrive at an answer using available data.
Ability to write clean and concise code in an object-oriented language and SQL
Ability to partner with cross-functional teams using strong written and verbal communication
Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
Initiative on solving problems and completing tasks in a reasonable timeframe
Strong written and verbal communication skills

Preferred Qualifications & Skills
10+ years of applied data science experience
Experience with Diesel Engines is a plus
C # or Java programming skills
Knowledge of LLMs
Hadoop, Spark, MapReduce, Hive
Education

Bachelor in a quantitative field is

Required;
Master's degree is a plus, and 2+ years of industry experience
Additional Job Board Information


PACCAR is an Equal Opportunity Employer/Protected Veteran/Disability and E-Verify Employer.
Hiring

Location:
Lewisville, TX
#LI-LW1


Nearest Major Market:
Dallas

Nearest Secondary Market:
Fort Worth

Job Segment:
Machinist, Data Modeler, Data Management, Information Technology, Manufacturing, Automotive, Data, Technology

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