We're looking for a hands-on Data Scientist to join our growing backend team. You'll be responsible for designing, training, and deploying machine learning models that power our predictive analytics and in-app insights. This is a unique opportunity to own the end-to-end modeling lifecycle.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
About XO Sports
XO Sports is building a next-gen B2C mobile platform for the online sports market, starting with the NBA and expanding into AFL, NRL, and NFL over the next 12 months. Our platform is powered by Azure cloud, leveraging a broad range of data services including Data Factory, Databricks, ADLS Gen2 and github to enabling us to ingest, transform data model for ML training. These insights can then be published real-time insights to fans and punters.
Role Summary
We’re looking for a hands-on Data Scientist to join our growing backend team. You’ll be responsible for designing, training, and deploying the machine learning models that power our predictive analytics and in-app insights. This is a unique opportunity to own the end-to-end modeling lifecycle—from feature engineering in Databricks to real-time model deployment—helping shape the future of sports analytics.
Hands-On Innovation & Model Vision
- Design & Iterate: Lead the development of object detection, classification, and segmentation models specifically tailored for high-stakes sports environments.
- Structured Experimentation: Run rigorous ablations and performance analyses to evolve model ideation within a data-driven framework.
- Azure Mastery: Use the Azure ecosystem (Databricks, Data Factory) to design, deploy, and tune ML experiments and endpoints.
- Edge & Performance: Profile and tune models for embedded targets, ensuring they thrive in real-time, mission-critical workflows.
- Predictive Analytics: Decipher complex patterns to facilitate data-driven decisions and evolve prediction workflows for inference and automated retraining.
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Technical Leadership & Strategy
- Strategic Interface: Collaborate with engineering leadership to define technical goals, scope work, and align ML development with product objectives.
- ML Assurance: Establish "Center of Excellence" (CoE) standards for ML development, including CI/CD pipelines, code quality, and system integration.
- Accountability: Own the ML team's delivery and quality, acting as a high-level advocate across engineering and product forums.
- Auditability: Produce clear technical documentation covering architecture, assumptions, and limitations to ensure operational confidence and compliance.
Qualifications & Experience
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Required
- Practical experience as a Data Scientist/ Machine Learning Engineer, with a proven track record of designing and deploying models for production services.
- Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or a related technical field.
- Deep Technical Stack: Mastery of Python and the Azure ecosystem (Databricks, SQL, Data Lake Gen2, Delta Tables).
- Mathematical Core: Strong foundation in math, probability, statistics, and complex algorithms.
- Communication: Ability to bridge the gap between deep technical implementation and executive-level briefings.
Highly Desirable
- Prior experience as a Lead Architect while remaining hands-on in the codebase.
- Expertise in MLOps tooling, experiment tracking, and automated workflow pipelines.
- Knowledge of contemporary practices in Trustworthy AI and model assurance.
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Perks & Benefits
- Significant Equity: Meaningful ownership and performance bonuses—we want you to grow alongside the founders.
- Career Acceleration: In 12 months here, you’ll touch more systems and wear more hats than in 3 years at a tech giant.
- Flexibility: A strong remote/office hybrid model that respects your work-life balance.
- Global Mobility: Full visa sponsorship for international candidates looking to move to Australia.
- Continuous Learning: Funded training and certifications to keep you at the bleeding edge.
- Purpose: One "Give-back" day per year to support your favorite charity.
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