Build/maintain anomaly detection model using statistical, machine learning, and data mining techniques. Design and implement AI-driven workflows to automate business intake processes, leveraging both low-code platforms (e.g., Copilot Studio) and code-based frameworks to enable intelligent comparison with historical requests and generate self‑serve recommendations. Partner with business stakeholders to understand objectives, gather requirements, and translate business needs into analytical solutions. Use programming languages (Python, Pyspark, SQL) to extract and prepare data, apply statistics and various advanced analytics along with business acumen to inform recommendations and insights from large datasets. Collaborate across AIML, data engineering, and analytics to deploy and monitor solutions at scale. Provide thought leadership and/or industry knowledge for own area of expertise and participate in knowledge transfer within the team and business unit. Share expertise and drive knowledge transfer through internal training, labs and runbooks Requirements

Undergraduate or advanced technical degree (e.g., math, statistics, engineering, finance, or computer science); graduate's degree preferred with progressive work experience 3+ years of relevant experience in analytics, data science and/or consulting, ideally in an influencing or advisory capacity Hands on modelling experience with supervised, unsupervised and other AI methods, including deep learning and neural networks Experience on Copilot Studio, Azure AI Foundry, Power Apps,



Power Automate tools is a must Demonstrated knowledge and application of analytical languages/tools/platforms such as Python / Pyspark, SQL, Tableau, PowerBI, Databricks, on large datasets with a track record of delivering business impact and results Experience delivering ML enablement (brown bags, workshops, office hours) aligned with internal learning pathways Ability to translate intake requests into technical plans and deliver self‑serve artifacts for business partners. Solid communication skills; open mindset—curious, collaborative, and evidence driven ‑driven Core Competencies

Demonstrates expertise in building and maintaining anomaly detection models using statistical and machine learning techniques, while effectively translating business needs into analytical solutions. Proficient in leveraging programming languages and tools to extract insights from large datasets and drive business impact. Highest-signal resume keywords

Anomaly Detection Model Development Machine Learning Techniques Python Programming Copilot Studio Experience Data Analysis and Visualization Hard Skills

Statistical Analysis Data Mining Techniques Supervised Learning Unsupervised Learning Deep Learning Neural Networks SQL Pyspark Tableau PowerBI Soft Skills

Strong Communication Skills Collaborative Mindset Curiosity Evidence-Driven Approach Industry Keywords

Analytics Data Science Business Intelligence ML Enablement Knowledge Transfer Tools & Technologies

Copilot Studio Azure AI Foundry Power Apps Power Automate Databricks

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📌 Data Scientist II (Winnipeg)
🏢 Jobtailor
📍 Winnipeg