Analytics Engineer - X

Xai
Palo Alto, CA
On-site

Who this role is best for

Best suited to mid-level data engineers with strong quantitative skills working in mission-driven, global-scale environments.

Best fit for

  • Mid-level data engineers with 4+ years of scalable pipeline experience and a strong analytical mindset
    — “4+ years of experience building production data pipelines and infrastructure at scale.
  • Candidates who thrive in small, high-impact teams and enjoy translating business needs into technical systems
    — “Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights.
  • Individuals with a background in quantitative fields and a track record of delivering reliable systems
    — “Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.

Things to consider

  • The role demands direct, hands-on contributions to global-scale systems and mission-critical work
    — “All employees are expected to be hands-on and to contribute directly to the company’s mission.
  • Strong communication is required to share knowledge concisely and accurately
    — “All employees are expected to have strong communication skills.

How to stand out

  • Highlight experience with real-time systems and data optimization in your resume and interviews
    — “Experience with real-time streaming systems and low-latency data processing.
  • Showcase your ability to deliver reliable, scalable data solutions with tangible outcomes
    — “This role combines strong software engineering practices with expertise in large-scale data processing.
  • Emphasize your statistical modeling and experimental design capabilities in your application materials
    — “Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement.
  • Demonstrate your ability to mentor others and share best practices in data engineering
    — “Mentor team members on best practices for scalable data engineering and quantitative problem-solving.
  • Include examples of your work with cloud services in data storage, processing, and orchestration
    — “Solid understanding of cloud services for data storage, processing, and orchestration.
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Design, implement, and optimize end-to-end data pipelines
  • Develop quantitative models and statistical frameworks
  • Build and maintain data infrastructure
  • Collaborate with product engineering, product, and operations teams
  • Conduct A/B tests, causal analysis, and performance evaluations
Typical background
4+ years of experience building production data pipelines and infrastructure at scaleBachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field

Skills & requirements

Required

PythonSQLDistributed Computing FrameworksStatistical MethodsPredictive ModelingHypothesis TestingExperimental DesignCloud Services For Data StorageData ProcessingOrchestration

Preferred

Real-time Streaming SystemsLow-latency Data ProcessingContributions To Open-source Data ToolsPublications On Large-scale Analytics SystemsReducing Operational CostsImproving System Efficiency Through Data Optimizations

Stack & domain

PythonSQLSparkKafkaFlinkHadoopStatistical MethodsPredictive ModelingHypothesis TestingExperimental DesignCommunicationProblem-solvingTeamworkLeadershipData EngineeringQuantitative AnalysisBusiness Decision-making

About the role

Original posting from Xai via Greenhouse

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

ABOUT THE ROLE:

We are seeking a skilled Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making. This role combines strong software engineering practices with expertise in large-scale data processing and advanced analytical methods to deliver reliable, scalable solutions across the organization. This is an opportunity to work on mission-critical systems that power quantitative decision-making at global scale.

RESPONSIBILITIES:

Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc.

Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement.

Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows.

Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights.

Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics.

Implement monitoring, alerting, and automation for data systems to support real-time decision support.

Mentor team members on best practices for scalable data engineering and quantitative problem-solving.

BASIC QUALIFICATIONS:

4+ years of experience building production data pipelines and infrastructure at scale.

Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).

Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.

Solid understanding of cloud services for data storage, processing, and orchestration.

Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.

Excellent problem-solving skills with a focus on delivering business impact through reliable systems

PREFERRED SKILLS AND EXPERIENCE:

Prior work in consumer technology, or social media domains.

Experience with real-time streaming systems and low-latency data processing.

Contributions to open-source data tools or publications on large-scale analytics systems.

Track record of reducing operational costs or improving system efficiency through data optimizations.

Have the ability to bridge engineering excellence with rigorous analytical approaches.

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Source: Xai careers (Greenhouse)

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