Data and AI Analyst
Toronto, Ontario, Canada
Stikeman Elliott
We are seeking an experienced Data Analyst with expertise in Generative AI (GenAI), Python, and data strategy implementation to join our team. This role will assist with shaping and executing our organization’s data strategy, helping us optimize how data is collected, processed, and utilized to drive business decisions. The ideal candidate will have experience with both traditional data science techniques and emerging AI technologies and will also have a good understanding of data governance, data infrastructure, and associated tools that support scalable data-driven operations.
Principal duties & responsibilities:
- Deliver on Data Strategy: Collaborate with senior leadership to create a robust data strategy that aligns with business goals, emphasizing data governance, quality, and scalability.
- Data Infrastructure and Tools: Help select and implement tools for data collection, processing, and storage, ensuring efficient, scalable data pipelines and cloud-based infrastructure.
- Data Integration and ETL: Assist with the extraction, transformation, and loading (ETL) of data from multiple sources, ensuring data consistency and availability for analytical and AI model-building purposes.
- Python Programming: Write, test, and optimize Python code for machine learning models, APIs, and automation tasks.
- Data Strategy Execution: Develop data management plans, including the development of metrics to measure success and efficiency of data utilization.
- Industry Awareness: Stay updated on trends in AI and data management, keeping our team at the cutting edge of technological advancements.
Required Skills and Qualifications:
- Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, or a related field.
- Strong experience in developing and deploying Generative AI models (e.g., GANs, transformers, LLMs) and applying them to real-world use cases such as NLP, synthetic data generation, and creative AI applications.
- Proficiency in Python and its associated data science and machine learning libraries (Pandas, NumPy, TensorFlow, PyTorch, Keras).
- Hands-on experience with data processing tools and ETL pipelines.
- Understanding of data management tools like Snowflake, BigQuery, Databricks, Fabric or similar technologies for storing and querying large datasets.
- Knowledge of machine learning algorithms and their implementation for predictive analytics, optimization, and business intelligence.
- Ability to design data architectures that align with business requirements and support scalable analytics and AI initiatives.
- Excellent problem-solving skills and the ability to translate business needs into data solutions.
Preferred Qualifications:
- Knowledge of API development for machine learning and AI model deployment, allowing for integration with business applications.
- Familiarity with data visualization tools such as Tableau, PowerBI, or similar platforms for reporting and insights delivery.
- Experience with data lake and data warehouse architectures.
Please Note: Our firm has a COVID-19 Vaccination Policy which requires all firm members to be fully vaccinated with a Health Canada approved COVID-19 vaccine. You will not be asked to disclose your vaccination status during the interview process. If you are offered employment, you will find a vaccination clause in your offer of employment providing that prior to commencing any employment with the Firm, you must be fully vaccinated for COVID-19 and provide proof of a Health Canada approved COVID-19 vaccination. The Firm will make reasonable accommodation efforts if you cannot be vaccinated due to medical, religious, or other grounds to the extent protected by applicable human rights legislation.
Stikeman Elliott is committed to accommodating people with disabilities as part of our hiring process. If you have special requirements, please advise Human Resources during the recruitment process.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: API Development APIs Architecture BigQuery Business Intelligence Computer Science Databricks Data governance Data management Data pipelines Data strategy Data visualization Data warehouse ETL GANs Generative AI Keras LLMs Machine Learning ML models Model deployment NLP NumPy Pandas Pipelines Power BI Python PyTorch Snowflake Tableau TensorFlow Transformers
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