Data Science Analyst

We are looking for a Data Science Analyst. This role is a 3 days Hybrid contract role in Mississauga.

As a Data Science Analyst, you will:

Analyze large structured and unstructured datasets to identify trends, patterns, and business insights.

Perform data cleansing, transformation, and feature engineering to support model development.

Develop, test, and maintain predictive and prescriptive models using statistical and machine learning techniques.

Support the deployment of analytical solutions into production environments in partnership with technology teams.

Contribute to the implementation of machine learning lifecycle processes, including development, testing, training, monitoring, and performance evaluation.

Collaborate with business, technology, and risk partners to understand requirements and translate them into analytical solutions.

Document methodologies, assumptions, and model results to support governance and review processes.

Present analytical findings and project updates to team members and stakeholders.

Continuously learn and apply emerging techniques in Machine Learning, Deep Learning, Large Language Models (LLMs), and Generative AI.

Qualifications

Master's degree or Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.

5+ years of experience in data science, machine learning, advanced analytics, or a related field.

Experience developing and evaluating machine learning models.

Working knowledge of ML/DL techniques and model development processes.

Proficiency in Python, SQL, Spark, PySpark, TensorFlow, or similar analytical and model-building tools.

Familiarity with LLMs and GenAI technologies.

Strong analytical, problem-solving, and communication skills.

Ability to work independently while collaborating effectively within cross-functional teams.

Preferred Skills

Experience supporting ML, AI, or GenAI initiatives in a production environment.

Familiarity with distributed data and computing platforms such as Hadoop, Hive, Spark, or cloud-based analytics platforms.

Exposure to banking, Retail Risk management, or financial services.

Basic understanding of capital markets, financial instruments, and quantitative modeling concepts.

Education

Bachelor's degree/University degree or equivalent experience in a STEM-related field. Advanced degree preferred.

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