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Data Scientist, Level 2

Job in Waller, Waller County, Texas, 77874, USA
Listing for: Daikin
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Location: Waller

Job Description

Daikin Comfort Technologies Mfg is seeking a professional, skilled individual for our Data Scientist position at our Waller, TX facility. The Data Scientist role at its core links business strategy to the data. The Data Scientist role at its core links business strategy to the data. He/she will transform structured or unstructured data into actionable information and predictive models to make a big impact across the organization.

This individual will break down the hairiest of problems by applying the full data science toolkit and provide insights to stakeholders across the organization to change minds and hearts. He/she will keep the customer front of mind in all of the work and optimize the customer experience, which will translate to creating long-term business value. As a pioneering Data Scientist at Daikin, he/she will influence the cultural change around how we use, talk about, and ultimately value our data assets, as part of a broader Digital Transformation.

Why

work with us?
  • Benefits are effective on day one for all full-time direct hires.
  • Training programs are available to help guide team members and develop new skills.
  • Growth Opportunities – there are immense opportunities to grow your career.
  • You will be part of a Global Company – our family brands are backed by Daikin Industries, Ltd.
Position Responsibilities may include:
  • Gather, process, clean, enrich, and integrate structured and unstructured data to build advanced models to turn data into insights; creatively analyze data to understand drivers of historical business performance and build predictive models to inform future business strategies
  • Deep understanding of our organization's data structure; look for ways to improve to enhance our ability to perform robust data analysis; create new data sets when there is little or no data available, to inform marketing analysis
  • Engage with third-party data providers to strengthen and enrich data models as needed; inform purchase of net new data
  • Deeply understand all sources of data across the enterprise, link to data strategy, and continually evolve ability to measure and track key data points to enable data-driven decisions
  • Collect and provide quantitative and qualitative information to measure effectiveness of marketing activities and answer strategic business questions
  • Analyze and discern campaign execution, targeting and optimization of marketing investment to deliver sales and operating profit across brands
  • Utilize visualization solutions to improve timeliness of data delivery and provide better visibility to decision makers to help them monitor, measure, or predict how the company is performing
  • Perform marketing research & analysis to inform customer targeting & segmentation, in addition to longitudinal tracking of Customer Lifetime Value across the enterprise
  • Assist with internal assessments of workflow processes to identify inefficiencies, especially those where Marketing is involved, and propose more efficient processes and procedures via process automation leveraging tech platforms
  • Assist with maintenance and management of Marketing SQL database and Snowflake cloud data warehouse
  • Provide data science support and ad hoc analysis to enterprise leadership as needed
  • Perform additional projects/duties to support ongoing business needs.
Nature & Scope:
  • Applies practical knowledge of job area typically obtained through advanced education and work experience
  • Encouraged to seek continuous improvements
  • Performs a range of mainly straightforward assignments
  • Works independently with general supervision
  • Problems faced are difficult but not typically complex
Knowledge &

Skills:
  • Strong analytical skills with attention to detail; strong knowledge of statistical analysis, machine learning process, computer science principles, and basic programming principles
  • Moderate data storytelling ability – ability to produce actionable information/insights, not just data crunching
  • Strong communication skills, both verbally and written, capable of communicating with people of many different levels of an organization
  • Knowledge of experimentation and testing of Minimum Viable Products to determine if proposed business…
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