We have an exciting long term contract opportunity for an Applied AI & Data Analytics Specialist / Data Scientist with one of our large scale transportation clients. This will be a hybrid role 2 days onsite per week in Toronto at Yonge & Davisville. The contract will run for 24 months to start with the anticipated start date of May 2025. 

Our client is embracing AI-driven technology innovations to enhance customer service, optimize operational efficiency, and improve the overall experience of customers and staff. They aim to leverage artificial intelligence (AI) and machine learning (ML) for advanced data mining, predictive analytics, and intelligent automation to drive data-driven decision-making and achieve their strategic objectives.

The Applied AI & Data Analytics Specialist / Data Scientist will be responsible for developing and implementing AI-powered analytics solutions. This includes leveraging machine learning algorithms, natural language processing (NLP), and deep learning models to extract insights, enhance predictive capabilities, and optimize business functions. The role will focus on applying AI techniques to improve service reliability, demand forecasting, and operational decision-making, ensuring a seamless and efficient transit experience.

Reporting to the Chief Enterprise Architect and taking day-to-day work direction from Project Management and Application Portfolio Managers, the Applied AI & Data Analytics Specialist / Data Scientist will be responsible for collaborating with cross-functional teams to identify business needs and implementing data-driven solutions, analyzing complex data models, developing and deploying machine learning models for predictive analytics including the transformation of large datasets using Azure Databrick and Apache Spark, creating data visualizations and dashboards using Power BI or similar tools.

The ideal candidate will have hands-on expertise in Azure Synapse and Azure Databricks environments, ensuring the efficient processing, analysis, and interpretation of complex datasets to drive data-informed decision-making.

Scope of Work

• Collaborate with cross-functional teams to identify business needs and implement data-driven solutions.
• Build, maintain, and optimize ETL pipelines in Azure Synapse Analytics.
• Process and transform large datasets using Azure Databricks and Apache Spark.
• Design, develop, and implement AI/ML models and advanced data analytics solutions.
• Develop and deploy machine learning models for predictive analytics.
• Work with large-scale data processing frameworks using Azure Databricks and Spark.
• Conduct exploratory data analysis, feature engineering, and predictive modelling.
• Create data visualizations and dashboards using Power BI or similar tools
• Ensure best practices in data governance, model performance, and scalable architectures.
• Stay up to date with the latest advancements in AI/ML and cloud-based analytics
• Other project duties as assigned

Mandatory Qualifications and Skills

• University degree or college diploma in a related field (e.g. - Computer Science, Data Science, Statistics) or equivalent experience
• 5+ years of experience in data science, machine learning and advanced analytics.
• Strong understanding of data modelling, ETL pipelines and big data solutions.
• Experience working with structured and unstructured data sources
• Hands-on experience with Azure Synapse and Azure Databricks
• Hands-on programming skills in Python, including experience with ML libraries such as Pandas, MumPy, Dask, GeoPandas, Google OR-Tools, PuLP TensorFlow/Pytorch etc.
• Experience building and deploying AI/ML models in Azure Machine Learning (AML) services.

Other Technical Skills

• Proficiency in Azure Synapse and Azure Databricks tools and environments.
• Strong programming skills in Python, Scala, or R.
• Expertise in Apache Spark and big data processing.
• Solid understanding of data lake architecture and data warehousing principles.
• Proven ability to derive actionable insights from complex datasets.
• Experience with statistical analysis, predictive modelling, and machine learning techniques.
• Advanced knowledge of SQL for data manipulation and querying.
• Experience with visualization tools like Power BI for reporting.
• Proven ability to derive actionable insights from complex datasets.
• Experience with statistical analysis, predictive modelling, and machine learning techniques.
• Advanced knowledge of SQL for data manipulation and querying.
• Experience with visualization tools like Power BI for reporting.
• Microsoft Certified: Azure Data Engineer Associate (DP-203).
• Microsoft Certified: Azure AI Engineer Associate (optional).