Data Science Lead Jobs in Arizona
Data Science Lead jobs in Arizona are open across Phoenix, Scottsdale, and Chandler and other Arizona metros, with employers like Amazon, CVS Health, and Matlen Silver hiring at every experience level. Find a role that fits below and apply directly.
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Infrastructure Engineer Lead
12+ Months (Extendable)
Chandler, AZ (Hybrid)
NO C2C/ONLY W2
Description:
The individual in this role is accountable for infrastructure data, context, and knowledge-related designs within one or more network and service domains that enable AI and deterministic automation outcomes in accordance with architectural governance, standards, and policies. This role facilitates delivery of technical context and data improvements by leading other infrastructure engineers and domain contributors in identifying source issues, defining remediation activities, and developing the templates, playbooks, documentation patterns, and supporting automation needed to improve trusted data and knowledge at source. Within the Data Knowledge pillar, this individual provides hands-on technical and network product expertise to help ensure configurations, telemetry, standards, policies, documentation, and operational knowledge are accurate, usable, and structured appropriately for downstream AI model consumption and deterministic automation use. This individual will demonstrate a high level of technical expertise across network products, service implementations, and operational context, while also demonstrating the ability to decompose issues or objectives into units of work that can be assigned to other team members. They advocate and advance more efficient solution delivery practices and evangelize strong design, engineering, and organizational practices that improve the trustworthiness and operational usefulness of context provided to AI and automation solutions.
Key Responsibilities:
- Confirm that business and technical context requirements are translated into actionable remediation plans, documentation patterns, templates, playbooks, and supporting guidance aligned to enterprise standards and policies.
- Lead technical efforts to identify and address data defects, documentation gaps, metadata issues, and operational knowledge weaknesses at source across network and service domains.
- Provide network product and service subject matter expertise to help data engineers and related teams define context assets suitable for AI model consumption and deterministic automation use.
- Guide the development of reusable templates, reference models, documentation structures, and technical knowledge patterns that improve context quality, consistency, and reuse.
- Mentor infrastructure resources on methods for improving source data quality, capturing operational knowledge, and documenting technical context in a way that supports trusted downstream consumption.
- Assist and mentor engineers by ensuring technical context artifacts and supporting data improvements comply with enterprise design, engineering, and governance expectations.
- Contribute to the creation and selection of functional and non-functional requirements for context, documentation, and data quality improvements within and across domains.
- Review and guide approaches for correcting recurring source defects through preventative and detective quality measures that improve long-term trust in AI-relevant data and knowledge.
Required Skills:
- Strong experience working with network products, infrastructure services, and operational implementations in a complex enterprise environment.
- Advanced technical understanding of network service behavior, configurations, telemetry, dependencies, and operational workflows required to interpret and improve source data and knowledge.
- Experience identifying and helping remediate data defects, metadata issues, or documentation quality gaps at source within infrastructure or service domains.
- Ability to partner effectively with data engineers and related teams to translate technical infrastructure knowledge into usable structured and unstructured context assets for AI and automation consumption.
- Strong knowledge of how documentation, standards, policies, configurations, runbooks, and operational records contribute to trusted context for AI models and deterministic automation.
- Experience creating or guiding templates, playbooks, reference artifacts, and documentation patterns that improve consistency and reuse across technical domains.
- Ability to assess data and knowledge fitness for downstream use, including completeness, accuracy, freshness, consistency, and operational relevance.
- Strong understanding of preventative and detective quality practices that help reduce recurring defects and improve confidence in source information.
- Experience decomposing complex technical objectives into actionable work items and guiding engineers or domain contributors through delivery activities.
- Ability to work across engineering, operations, architecture, product, and data stakeholders to align context improvement efforts with enterprise standards and delivery priorities.
- Familiarity with enterprise governance, standards, and controlled delivery practices in a regulated environment.
- Strong written and verbal communication skills with the ability to explain technical context, documentation requirements, source issues, and knowledge gaps clearly.
- Experience supporting documentation or knowledge capture efforts that improve operational supportability, traceability, and downstream usability.
- Strong analytical thinking, attention to detail, and problem-solving skills in support of trusted, high-quality technical context.
- Experience working in a fast-paced and complex global environment with evolving priorities and multiple domain dependencies.
About Matlen Silver
Experience Matters. Let your experience be driven by our experience. For more than 40 years, Matlen Silver has delivered solutions for complex talent and technology needs to Fortune 500 companies and industry leaders. Led by hard work, honesty, and a trusted team of experts, we can say that Matlen Silver technology has created a solutions experience and legacy of success that is the difference in the way the world works.
Matlen Silver is an Equal Opportunity Employer and considers all applicants for all positions without regard to race, color, religion, gender, national origin, age, sexual orientation, veteran status, the presence of a non-job-related medical condition or disability, or any other legally protected status. If you are a person with a disability needing assistance with the application or at any point in the hiring process, please contact us at email and/or phone at: info@matlensilver.com // 908-393-8600
At The Matlen Silver Group, Inc., W2 employees are eligible for the following benefits:
Health, vision, and dental insurance (single and family coverage)
401(k) plan (employee contributions only)
See All 7 Data Science Lead Jobs in Arizona
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Find Data Science Lead JobsData Science Lead Jobs by City in Arizona
Where Arizona roles are concentrated, by current openings.
Data Science Lead Job Market in Arizona
A snapshot from current Arizona openings, updated as new roles post.
Who's Hiring
- Amazon1

- CVS Health1

- Matlen Silver1

- Nextiva1

- Rocket Money1

Top Industries Hiring
- Banking & Financial Services1
- Construction & Real Estate1
- Education1
- Healthcare & Medical Services1
- Staffing & Recruiting1
What Arizona Employers Look For
The qualifications that appear most often in data science lead jobs across Arizona.
- 5+ years of experience in data science with at least 2 years in a lead or senior role
- Proficiency in Python or R along with SQL for data manipulation and modeling workflows
- Experience deploying machine learning models to production environments at scale
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for data infrastructure
- Demonstrated ability to mentor junior data scientists and manage cross-functional projects
- Graduate degree in statistics, computer science, mathematics, or a closely related field
Data Science Lead Jobs in Arizona: Frequently Asked Questions
How many data science lead jobs are there in Arizona?
There are 7+ data science lead openings in Arizona on Migrate Mate as of June 2026, with the most roles in Phoenix, Scottsdale, and Chandler. New positions post regularly as employers across Arizona hire.
How much do data science leads make in Arizona?
Data science leads in Arizona earn a median of about $107,240 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $65,200 for the lowest 10% to over $161,730 for the top 10%. Pay rises with experience, specialty, and employer.
Which Arizona cities have the most data science lead jobs?
Phoenix, Scottsdale, and Chandler have the most data science lead openings in Arizona right now, with additional roles spread across smaller metros statewide.
Which companies hire data science leads in Arizona?
Employers hiring data science leads in Arizona include Amazon, CVS Health, and Matlen Silver, based on current listings on Migrate Mate as of June 2026.
Are there remote data science lead jobs in Arizona?
Yes. About 29% of data science lead openings tied to Arizona are remote or hybrid as of June 2026. The rest are on-site roles based in Arizona metros.
How do I apply for data science lead jobs in Arizona?
You can apply to data science lead jobs in Arizona directly on Migrate Mate. Search the listings above, find roles that match your experience and preferred Arizona location, then apply to each one that fits.
See All 7 Data Science Lead Jobs in Arizona
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