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Head Data Science Jobs in Arizona (NOW HIRING)

The Head of People Analytics & Datais a Senior Vice President role that is responsible forleading U ... Build talent in advanced analytics, data science, and data strategy. * Create a culture of ...

The Head of Growth Marketing is responsible for accelerating profitable customer acquisition ... Collaborate with Finance and Data Science to refine marketing measurement, including attribution ...

The Head of Growth Marketing is responsible for accelerating profitable customer acquisition ... Collaborate with Finance and Data Science to refine marketing measurement, including attribution ...

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Head Data Science information

See Arizona salary details

$21.8K

$106.9K

$198.1K

How much do head data science jobs pay per year?

As of Aug 6, 2026, the average yearly pay for head data science in Arizona is $106,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,252.00 and $144,660.00 per year, depending on experience, location, and employer.

What does a head data science do?

A Head of Data Science is responsible for leading and managing the data science team within an organization. They oversee the development and implementation of data-driven strategies, ensuring that the team delivers valuable insights and predictive models to support business goals. This role involves collaborating with other departments, setting the vision for data initiatives, and ensuring best practices in data analysis and machine learning are followed. Additionally, the Head of Data Science often mentors team members and helps shape the organization's overall data strategy.

What are some common challenges faced by a head data science when building and leading a data science team?

As a Head of Data Science, one of the main challenges is balancing strategic leadership with hands-on technical guidance. You'll often need to align the team's goals with broader business objectives while ensuring that team members have the right mix of skills and resources. Additionally, fostering effective collaboration between data scientists, engineers, and business stakeholders can be complex, especially in cross-functional environments. Managing expectations around project timelines and communicating technical insights in a clear, actionable way are also key aspects of the role.

What are the key skills and qualifications needed to thrive as a head data science?

To thrive as a Head of Data Science, you need advanced expertise in statistics, machine learning, data modeling, and a strong background in computer science or a related quantitative field, often supported by a master's or Ph.D. Proficiency with programming languages like Python or R, big data platforms such as Hadoop or Spark, and familiarity with cloud-based analytics tools are typically required. Strategic leadership, excellent communication skills, and the ability to mentor and inspire teams are crucial soft skills for this role. These abilities are essential to drive data-driven decision-making, foster innovation, and align analytics initiatives with organizational goals.

What is the difference between Head Data Science vs Data Science Manager?

AspectHead Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsTeam management, project delivery, coordinating data science projects
Required SkillsAdvanced analytics, leadership, strategic planningTeam management, technical expertise, project management
ExperienceSenior data science background, leadership rolesData science experience with managerial responsibilities
Work EnvironmentExecutive level, cross-departmental collaborationTeam-focused, project-oriented

The Head Data Science typically holds a strategic, leadership role overseeing the entire data science function, while the Data Science Manager focuses on managing teams and project execution. Both roles require strong technical backgrounds, but the Head Data Science emphasizes vision and strategy, whereas the Data Science Manager concentrates on operational management.

What are the most commonly searched types of Data Science jobs in Arizona? The most popular types of Data Science jobs in Arizona are:
Infographic showing various Head Data Science job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $106,916 per year, or $51.4 per hour.

Senior Software Engineer II (TASER Data Science)

Axon

Scottsdale, AZ

$123K - $162K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago


Axon rating

8.8

Company rating: 8.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

14th of 156 rated electronics manufacturers


Job description

Your Impact

Law enforcement agencies need training systems informed by real data about how officers perform in the field. We've spent the last few years collecting that data and validating the data products that create actionable insights that trainers can use to make encounters more effective, less injurious, and safer for everyone involved. We've shipped the simple models, but now we need to get our customer-validated models into production. Your job is not just to ship them, but to ensure that we have a strategic pipeline to continue delivering data products for our customers for years to come. What works in research needs to be production-grade, reliable, and reusable.

We're a small, technically deep team embedded in Axon's TASER pillar. Our work spans hardware telemetry and behavioral science - we analyze TASER device data, build models that drive training recommendations for law enforcement agencies, and ship the analytical tools that get those insights to the people who can act on them. Our analyses reach the C-suite. Our models become user-facing features. We're working toward Axon's Moonshot: reduce fatal officer-involved shootings by 50% in the next decade.
The head of product was a Staff Engineer. Our TPM ran a 60-person engineering organization. Both product managers have quantitative degrees - applied mathematics and engineering. Our program manager for TREND is a former state police lieutenant with over 30 years of experience in law enforcement. Our designer is part of the team, not separated from it. We built this team to cover the full space - engineering, data, product, and domain - and this hire is the next deliberate addition.
This is the opposite of a silo - and it comes with a tradeoff: you won't always have another SWE in the room, so you'll need to be technically self-sufficient. What you get in return is a team with more depth of experience per person than most engineering environments you've worked in.


What You'll Do

Location: This role is based out of one of our US-based offices (Seattle or Scottsdale) and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation.
Reports to: Director, TASER Data Science

  • Build and ship data products: dashboards, metrics systems, and recommendation tools that drive real decisions
  • Own production ML deployment - bring models from research to reliable production systems with monitoring, versioning, and operational rigor
  • Build and own data pipelines from TASER device telemetry through to analytics surfaces used by agencies and internal stakeholders
  • Set technical direction for the team's engineering practices - the data scientists here write code and want to do it better; you'll be the senior engineering voice they've been missing
  • Work across the full stack - device-side data ingestion through user-facing analytics - and move between projects to build breadth
  • Use AI tools as a core part of your development workflow, not a novelty
 What You Bring

Must-haves:

  • You write production code at a high standard - strongly typed, comprehensively tested, designed for the people who will maintain it after you. We write Python like software engineers, not data scientists.
  • You've deployed and operated ML systems in production: model serving, monitoring, failure handling, and the operational rigor that keeps them running
  • You identify the most important technical work and go after it - you've shaped technical roadmaps, influenced peers and organizational direction, and moved goals forward with or without explicit direction
  • You define the problem as much as you solve it - you thrive in a team where requirements evolve as you learn, and you see that as a feature, not a bug
  • You've worked with real-world messy data: device logs, behavioral data, event streams, or similar

Strong preferences:

  • Advanced degree in a quantitative or analytical field - PhDs are very welcome, we already have three
  • Intellectual background outside computer science is genuinely valued here: statistics, physics, engineering, biology, economics, linguistics, philosophy - it doesn't have to be a "hard science." We hire for intellectual diversity because it makes the work better.
  • Hands-on experience with ML production tooling: model registry, serving infrastructure, pipeline orchestration, and model monitoring
  • Experience with cloud data platforms in an ML context (Azure ML, Databricks, Snowflake) and batch or streaming pipeline architecture
  • Experience with hardware-adjacent data: device telemetry, IoT event logs, or similar
 Benefits that Benefit You
  • Competitive salary and 401k with employer match
  • Discretionary paid time off
  • Paid parental leave for all
  • Medical, Dental, Vision plans
  • Fitness Programs
  • Emotional & Mental Wellness support
  • Learning & Development programs
  • Employee Resource Groups (ERGs)
  • And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.


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