Equity Markets Data Scientist (GenAI, Python)

BeachHead Inc.; Toronto; On-site; CAD 96,000 - 110,000; Full time

Job summary

BeachHead Inc. is seeking a Data Scientist (Banking/Python/AI) to influence equity market AI initiatives. You will work with Azure Databricks to analyze large datasets, develop AI use cases, and deliver actionable insights to business stakeholders.

The role requires 3–5 years in data analytics or data science, strong Python/SQL skills, and familiarity with AI/GenAI projects in Capital Markets. Collaboration with data engineers and business partners is essential.

Qualifications

• 3–5 years in data analytics, BI or data science roles.
• Strong Python and SQL with ability to extract insights from large datasets.
• Experience with AI/ML or GenAI initiatives and Azure Databricks familiarity.

Responsibilities

• Analyze large datasets in Azure Databricks to identify trends, insights and opportunities.
• Support the development of AI and GenAI use cases across Equity Markets.
• Use Python to prepare, clean, transform, and analyze data for AI applications.
• Collaborate with stakeholders to map business needs to technical solutions.
• Research, evaluate, and summarize information using AI-enabled tools.
• Prepare datasets and workflows supporting language models and AI models.
• Extract actionable insights and communicate findings effectively.
• Collaborate with data engineers to leverage Azure Databricks as the enterprise data platform.

Skills

Python

SQL

Data analytics

GenAI

Education

Bachelor's degree in a quantitative field

Tools

Azure Databricks

Microsoft Copilot Studio

LangChain

Job description

BeachHead Inc. is seeking a Data Scientist (Banking/Python/AI) to influence equity market AI initiatives. You will work with Azure Databricks to analyze large datasets, develop AI use cases, and deliver actionable insights to business stakeholders.

The role requires 3–5 years in data analytics or data science, strong Python/SQL skills, and familiarity with AI/GenAI projects in Capital Markets. Collaboration with data engineers and business partners is essential.