Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.
About the role
As a Data Scientist at Sporty, you will build and productionize data-driven ML systems that enhance personalization, search, and recommendation experiences, with a clear focus on measurable business impact. The role combines advanced analytics, Python-based modelling, and cloud engineering to solve real-world problems at scale in a fast-paced product environment.
Our Stack
- SQL
- Python
- AWS/Azure/GCP
What you'll be doing
- Utilize advanced algorithms and data mining techniques to build personalized recommendation systems, optimizing product and service recommendations to enhance user experience and improve business conversion rates.
- Develop and productionize ML/AI systems across multiple domains — including search ranking, recommendation, and content intelligence — that directly impact user growth and business outcomes.
What you'll bring
- Hands-on experience applying statistical and ML models to real business problems, with measurable impact on revenue or key business outcomes
- Advanced understanding of Python and the quantitative analysis ecosystem in Python
- Strong foundation in probability theory, statistics, machine learning, and linear algebra
- 2+ years of experience as a data scientist, quantitative researcher, quantitative analyst, or another relevant role
- Knowledge of SQL and experience with relational databases
- Proficient with AI tools and agents as part of daily development workflow; this role regularly leverages AI-assisted development to accelerate delivery
- Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology, or Engineering
- Project and stakeholder management experience is preferred
Even better if you have
- Apache Spark
- Experience working in cloud platforms (AWS, GCP, Microsoft Azure)
- Relevant knowledge or experience in the gaming industry
- Solid computer science background
What’s in it for you
- Sporty is a remote first company in pursuit of sustainability
- A competitive salary + individual performance based bonuses every quarter
- 28 days paid annual leave
- Our core working hours are 10am-3pm in your local time zone with flexibility outside of this
- Referral bonuses & flash bonuses
- Top of the line equipment
- Annual company retreats to provide great internal networking opportunities
Interview Process
- Remote video screening with our Talent Acquisition Team
- Online home assignment
- Remote video interview with Team Members (3x45 Mins)
If you're interested, we encourage you to apply! Every application is reviewed by a member of our team (AI is not used in our recruitment process), and we aim to respond within 48 hours.
*We are committed to maintaining a fair, secure and authentic recruitment process. Applications submitted using false, misleading or fraudulent information, including impersonated or fake profiles, will not be considered. Where reasonably necessary to protect the integrity and security of our recruitment process, we may verify a candidate’s identity and/or the accuracy of information provided during the recruitment process. Any such checks will be carried out in a proportionate and appropriate manner and in accordance with applicable data protection and employment laws.
Similar Jobs
Cloud • Security • Software • Cybersecurity • Automation
Conduct advanced application security research across GitLab’s DevSecOps and AI-powered platforms. Identify and exploit novel, systemic, and chained vulnerabilities; develop proof-of-concept exploits, testing methodologies, and research automation; assess AI attack vectors and open-source dependencies; drive remediation and security improvements; advise engineering teams, contribute to roadmaps, mentor researchers, and share findings with the security community.
Top Skills:
Duo Agent PlatformGitlabGitlab DuoGoPythonRubyRustTypescript
Cloud • Security • Software • Cybersecurity • Automation
Conducts advanced application security research across GitLab’s DevSecOps and AI-powered platforms. Responsibilities include discovering and exploiting systemic vulnerabilities, penetration testing, developing proof-of-concept exploits, researching AI and agentic security threats, building automated research tooling, coordinating remediation, mentoring security professionals, and communicating findings to engineering and security communities.
Top Skills:
Ai FrameworksDevsecopsDuo Agent PlatformGitlabGitlab Duo ChatGoPythonRubyRustTypescript
Automotive • Professional Services • Software • Consulting • Energy • Chemical • Renewable Energy
Design and coordinate electrical systems for commercial, industrial, laboratory, and technical facilities from concept through construction. Lead Revit/BIM-based design, coordinate external engineering firms and vendors, review documentation, support budgeting and commissioning, and maintain design intent. Provide expertise in power distribution, lighting, low-voltage systems, equipment integration, safety compliance, facility troubleshooting, and energy-efficient building systems.
Top Skills:
AutocadBimBluebeamBuilding Automation Systems (Bas)Electrical EquipmentFire Alarm SystemsHvac ControlsLighting SystemsLow-Voltage SystemsMs ProjectNecNfpaOshaPower Distribution SystemsRevit
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
