Our Mission at Tactable

What if you could build software that didn’t just scale, but transformed entire organizations?

At Tactable, this is what drives us. We’re building a world-class cloud, data, and API engineering firm with a mission to power the most influential tech of tomorrow, through expert-led delivery, strong partnerships, and a relentless focus on quality.

We don’t just consult. We build.

Founded by engineers who care deeply about people, process, and product, we go beyond just solving problems. We embed with clients, work across full project lifecycles, and operate at the speed of startups while upholding the rigor of enterprise-grade engineering.

From financial institutions to emerging tech ventures, our work is behind some of the most mission-critical systems in production today, and we’re just getting started. With growing demand from top-tier clients and a strong runway for expansion, we’re building a team of curious, ambitious developers who want to build meaningful things with meaningful people.

Take a look at tactable.io to learn more about our work and what sets us apart.

The Role: Data Scientist

We are looking for a Data Scientist to guide the ethical, transparent, and compliant development of AI systems, particularly LLM and RAG-based solutions. This role focuses on ensuring AI fairness, accountability, and trustworthiness through proactive governance and best practices.

What You’ll Do

End-to-End Data Science + ML Development

• Establish and enforce Responsible AI frameworks to ensure fairness, transparency, and bias mitigation across all AI initiatives.
• Oversee LLM and RAG evaluation practices to align model performance with ethical and regulatory standards.
• Develop and maintain prompt governance policies to ensure responsible use of prompt engineering techniques.
• Collaborate with technical and legal teams to perform risk assessments for data usage, model outputs, and content safety.
• Drive AI ethics education and awareness across teams, ensuring adherence to global Responsible AI principles.
• Monitor industry trends, frameworks, and compliance requirements to continuously improve AI governance practices.

Technical Leadership

• Lead critical aspects of the ML lifecycle, from experimentation to deployment and monitoring
• Contribute to or integrate with platforms like IBM Watson Next for enterprise-grade AI solutions
• Build and maintain reusable components for feature engineering, model evaluation, and deployment
• Mentor junior data scientists through code reviews, best practices, and collaborative experimentation
• Create internal tooling and documentation to support scalable and reproducible science
• Act as a data scientist who codes, contributing directly to production-level codebases

Client & Project Exposure

• Work directly with client product, engineering, and compliance teams to deliver robust, auditable AI solutions
• Rotate across domains (e.g., finance, trading, enterprise tech) every 6–12 months, applying ML to diverse business problems
• Lead greenfield modeling projects, legacy system modernization, and ML-driven product development
• Act as a strategic partner, helping shape AI/ML product roadmaps and ensuring alignment with regulatory and ethical standards

What You Bring

Must-Have Experience

• 7+ years in AI/ML strategy, governance, or applied data science, including 2+ years focused on Responsible AI, model evaluation, or LLM risk management
• Strong understanding of Responsible AI principles, including fairness, accountability, transparency, explainability, and privacy in AI systems
• Experience designing and implementing evaluation frameworks for RAG (Retrieval-Augmented Generation) systems
• Hands-on experience with LLM evaluation and prompt governance frameworks (e.g., Ragas, TruLens, Giskard, OpenAI Evals) and chatbot quality metrics
• Proven track record implementing AI risk assessment, bias detection, and compliance controls within production AI or enterprise environments
• Familiarity with ethical AI policy design, model documentation (Model Cards, System Cards), and regulatory standards such as EU AI Act or NIST AI RMF

Bonus Points For

• Experience with Python programming and building reusable Python libraries (functions, classes)
• Exposure to advanced agent-based AI systems or newer orchestration tools (e.g., Semantic Kernel, Haystack)
• Familiarity with Agile/Scrum practices and tools like Jira and Confluence
• Awareness of AI governance, bias mitigation, and responsible AI frameworks

Why You’ll Love This Role

• Growth-First Culture: From custom career paths to project rotation, we design roles around your goals, not just business needs.
• Full Ownership & Impact: You’ll own critical parts of delivery, architecture, and technical decision-making. No red tape, no silos.
• Tight-Knit Team: We’ve built a culture of trust, collaboration, and curiosity. Whether it’s team lunches, hack days, or a new internal tool, we move as one unit.
• Real Work, Real Users: We’re not building MVPs that sit on a shelf. You’ll work on systems that millions rely on, every day.
• Flexibility with Structure: We’re a hybrid-first team with a strong appreciation for in-office collaboration, especially at our downtown Toronto HQ. We encourage in-person presence to foster mentorship, connection, and collaboration.

Why This Might Not Be a Fit

• You’re looking for narrowly scoped responsibilities or long-term focus on a single domain
• You prefer a rigid hierarchy with formal titles and isolated workstreams
• You’re more comfortable in a vendor-style delivery model than deep technical partnerships

Compensation, Benefits & Perks

• Salary Range: Competitive and flexible, based on experience and fit for the role.
• Comprehensive health and dental plan
• Generous PTO and holidays
• Laptop & home office equipment provided
• Career coaching and personalized development plans
• Regular social events, team outings, and wellness activities

Ready to Build the Next Generation of Data Infrastructure?

No cover letter required. Just apply, and let’s start building.