
Decision Intelligence Lead
TXFull-time$124–233K/yrPosted 1w agoStill listed 1 day ago
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Job overview
The Decision Intelligence Lead drives product strategy, roadmap, and delivery of executive analytics solutions that turn global operations initiatives into measurable business outcomes, translating complex data into actionable dashboards, scorecards, and interactive applications for enterprise decision‑making.
Skills & qualifications
Skills
Qualifications
Full job description
Job Description
The Decision Intelligence Lead, within the Operations Intelligence & Analytics organization, drives the product strategy, roadmap, and delivery of executive analytics solutions that translate Global Operations initiatives into measurable business outcomes. This role transforms complex operational data into actionable insights delivered through dashboards, scorecards, and interactive applications that improve decision-making, performance, and efficiency across the enterprise.
As a key partner to leaders across Supply Chain, Manufacturing, Quality, Regulatory Affairs, and other Global Operations functions, the Decision Intelligence Lead operates with a product-oriented approach to analytics, overseeing solutions from strategy and requirements through deployment and continuous enhancement. The ideal candidate combines expertise in business intelligence, modern data platforms, and advanced analytics with the ability to translate business needs into scalable, user-centric solutions that influence executive strategy and operational performance.
Responsibilities:
- Build and own the product roadmap, including the executive insights dashboard, data-rich executive summaries, and balanced scorecard reporting.
- Apply product strategy, management and UX principles to design scalable and intuitive data products with the user in mind.
- Develop decision intelligence products within Power BI and Microsoft Fabric, including semantic models, KPI frameworks, dashboards, and executive summaries that provide actionable insights into the health and performance of the global operations network.
- Build interactive scenario planning applications, incorporating predictive models to support trade-off analysis and forward-looking decision-making.
- Automate repeatable data extraction, preparation and transformation workflows using Python and SQL.
- Integrate ERP data from SAP, Oracle and additional disparate data sources into cohesive, consumable decision intelligence products.
- Apply predictive analytics and AI/ML techniques, where appropriate, to enhance operational forecasting, risk identification, scenario simulation, and decision support capabilities.
- Use standard DevOps tools, including GitHub, Confluence, and Jira, throughout the product development lifecycle.
Qualifications
- Bachelor's degree in Data Engineering, Data Science, Computer Science, Statistics, or a related field, or equivalent professional experience; Master's degree preferred.
- 8+ years of experience in data science, business intelligence, or analytics, with deep expertise in modern BI architecture and tools.
- Expertise in Power BI, including proficiency in DAX for building measures, KPIs, and time-intelligence calculations; broad experience in other tools such as Spotfire and Qlik.
- Highly proficient in Python (e.g., pandas, NumPy) and SQL, with hands-on experience data wrangling across disparate sources.
- Hands-on experience developing front-end/interactive applications using low-code and full-code frameworks such as Power Apps, Plotly Dash, or React.js.
- Experience leveraging DevOps and collaboration platforms, including GitHub, Confluence, and Jira, to support agile delivery, version control, documentation, and product lifecycle management.
- Strong executive communication, data storytelling, product strategy, and UX design skills, with a demonstrated ability to transform complex data into intuitive user-centric analytics products.
- Previous experience with unified analytics and lakehouse platforms such as Microsoft Fabric or Databricks, and familiarity with broader cloud data ecosystems (AWS, Snowflake).
- Experience working within large matrixed organizations, understanding business workflows and leveraging data from enterprise ERP platforms (e.g., SAP, Oracle).
Preferred Qualifications:
- Previous experience supporting global supply chain, manufacturing, quality, or regulatory operations in a complex enterprise environment.
- Familiarity with native GenBI capabilities (e.g., Copilot in Power BI/Fabric) and GenAI application development process.
- Practical experience across the ML lifecycle, including feature engineering, model selection, training and validation, deployment, and performance monitoring/retraining, using frameworks such as scikit-learn, XGBoost, or equivalent.
- Relevant Microsoft Fabric, cloud or data engineering certifications such as MS DP-600 or MS DP-700.
Additional Details
This job has a full time weekly schedule. Applications for this job will be accepted until at least October 14, 2026 or until the job is no longer posted.
The full-time equivalent pay range for this position is $124,160.00 - $232,800.00/yr plus eligibility for bonus, stock and benefits. Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locations
Agilent Technologies, Inc. is an Equal Employment Opportunity and merit-based employer that values individuals of all backgrounds at all levels. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to sex, pregnancy, race, religion or religious creed, color, gender, gender identity, gender expression, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, registered domestic partner status, age, sexual orientation, military or veteran status, protected veteran status, or any other basis protected by federal, state, local law, ordinance, or regulation and will not be discriminated against on these bases. Agilent Technologies, Inc., is committed to creating and maintaining an inclusive in the workplace where everyone is welcome, and strives to support candidates with disabilities. If you have a disability and need assistance with any part of the application or interview process or have questions about workplace accessibility, please email [email protected] or contact +1-262-754-5030. For more information about equal employment opportunity protections, please visit www.agilent.com/en/accessibility.
Travel Required:
10% of the Time
Shift:
Day
Duration:
No End Date
Job Function:
Administration
How this job compares
Set against the 1,733 open Product Strategy jobs on Olive Jobs, counted October 29, 2026.
- Pay
- This posting$124–233K/yr
- Texas median$135–241K/yr55 salary ranges
- US median$141–235K/yr1,421 salary ranges
This range's midpoint, $178K, is 9% below the Texas median midpoint ($196K) — in the middle half of Product Strategy salary ranges in Texas.
- Openings
- Olive Jobs lists 74 open Product Strategy jobs in Texas and 1,733 across the US. 10% of them nationwide are listed as remote or flexible.
- Hiring the most in Texas
- Deloitte11 open
- Accenture5 open
- Realtor.com4 open
- Experience
- This posting asks for at least 8 years of experience; Product Strategy postings that state a minimum ask for 7 years at the median (1,440 postings).
- Education
- 423 of the 1,733 open Product Strategy jobs (24%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 29, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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