Top Analytics Jobs in Ottawa

Support the analytics lifecycle by building and automating reports, analyzing data, and delivering actionable insights. Develop and maintain SSRS reports, write SQL queries, create VBA macros for automation, manage stakeholder relationships, and work independently on moderate-scope projects with general guidance.

Lead credit strategy and portfolio performance across the full credit lifecycle. Define pricing and underwriting frameworks, own IRR and cohort metrics, align credit strategy with Finance/Product/Sales, and ensure analytics drive measurable business impact. Influence executive stakeholders and manage teams to optimize risk-adjusted returns and portfolio health.

Design and deliver scalable analytics solutions by integrating disparate datasets, authoring and optimizing complex SQL, owning semantic layer and reporting, applying software engineering best practices, and partnering with Finance and business stakeholders to produce actionable insights and dashboards.

Lead end-to-end process mapping and analysis using BPMN and process/task-mining tools to identify inefficiencies, create As-Is/To-Be documentation, define BRDs, model future-state scenarios, and drive cross-functional implementation with executive reporting.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Design and build end-to-end data solutions and pipelines using modern cloud platforms; ingest, transform, and make data available for BI and downstream consumers. Partner with business stakeholders, implement CI/CD, testing, observability, and documentation, triage performance issues, and support delivery across client engagements.

The GTM Analytics Lead will drive data-driven decisions across marketing, sales, and finance, optimizing performance and ensuring sustainable revenue growth through analysis and real-time insights.

Assess and document current and target Martech architecture, identify redundancies and integration gaps, define unified data/process flows and integration patterns, recommend consolidation and AI-driven platform strategy, support implementation planning and governance, and produce architecture documentation to guide execution teams.

As a Senior Full Stack Software Engineer, you will own product features, design scalable systems, mentor teammates, and ensure coding excellence while collaborating with cross-functional teams.

Own analytics enablement by translating stakeholder questions into trusted, reusable metrics and semantic models. Build and maintain the metrics/semantic layer, validation, documentation, AI-accessible datasets, and pipelines to ingest new sources. Enable self-serve analytics and agentic LLM querying (Claude) while partnering with product, GTM, and executives.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

The Account Executive will develop and implement sales strategies, manage relationships with vendors, and drive growth through effective prospecting and client engagement.

As Analytics Lead, you'll drive data-informed decision-making, lead measurement strategies, mentor teams, and oversee analytics infrastructure, impacting client strategies.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Lead marketing analytics as the architect of the data-driven growth engine: build BigQuery data schemas, predictive models (attribution, MMM, LTV), agentic AI monitoring, automated orchestration, executive BI, and target-setting frameworks to optimize demand generation and funnel quality across GTM.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As an Engineering Manager, you'll lead a remote team, manage MLOps projects, ensure high performance, and mentor engineers while driving product strategies.

Lead design and delivery of Workday reporting and analytics for AMS clients: build advanced/matrix/trending/composite reports, dashboards, Discovery Boards, Worksheets, and complex calculated fields; gather requirements, optimize reports, mentor junior consultants, and provide Workday best-practice guidance.

As a Software Engineer, you'll build scalable micro-services, work with large data sets, and optimize performance, focusing on distributed systems and real-time analytics.

Lead technical strategy and hands-on implementation for Faire's data platform. Architect and scale ETL/ELT, streaming and batch pipelines, data warehousing, orchestration, monitoring, cost optimization, security, and governance. Mentor teams, prioritize platform roadmaps, and partner with product, analytics, and data science to enable self-serve data capabilities across the company.

The Director of eCommerce and Marketing Analytics will transform data into insights, lead analytics across multiple business functions, and establish AI-enabled workflows to drive decision-making.

Lead complex people-analytics work: design actionable dashboards, apply rigorous research methods, translate analysis for executives, advise HR leaders, build AI-driven workflows, and work hands-on with Visier, Snowflake, SQL, and Python/R.

Lead analytics engineering for TravelIQ and Arcadis Tolling by designing analytics architecture on Microsoft Fabric, building curated analytical data models, and delivering customer-facing Power BI reports. Combine near-real-time and historical operational data, ensure data quality and governance, and identify opportunities for new embedded analytics and data-driven product features.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

Embed with client engineering teams to deploy, integrate, and scale enterprise generative AI solutions. Build agentic systems, train and serve LLMs with Vertex AI, integrate models with BigQuery/AlloyDB/Spanner, implement streaming inference pipelines, and ensure operational reliability while collaborating with stakeholders to translate business goals into production-grade architectures.