Bilingual Junior Data Scientist

Nexus Systems Group Inc.; Toronto; Hybrid; CAD 80,000 - 100,000; Full time

Job summary

A technology solutions provider in Toronto is looking for a bilingual Data Scientist to enhance AI and machine learning initiatives. Responsibilities include working on RAG systems and analyzing complex data. The candidate should have relevant experience in data science and proficiency in Python and SQL. This role offers hybrid work arrangements and the chance to contribute to high-impact projects.

Qualifications

• 1-2 years of experience in LLM and RAG.
• Experience with data engineering and data pipeline skills.
• Strong foundation in data mining and data cleaning.

Responsibilities

• Assess and enhance the French version of the RAG system.
• Analyze large, complex datasets in structured and unstructured formats.
• Develop innovative approaches to solve clients’ analytics problems.

Skills

Bilingual proficiency in English and French

Experience with Natural Language Processing (NLP)

Hands-on experience with Python (Pandas, Scikit-Learn, NumPy)

Experience with SQL (SQL Server, PostgreSQL, BigQuery)

Experience with Cloud and Big Data tools

Education

Post-secondary education in STEM disciplines

Job description

Overview

Location: Toronto. Work arrangements: Hybrid (2 days in office) potentially changing to 3 days in office – TBD. Contract Duration: ASAP to 11/28/2025. Extension: Yes, depending on business needs and funds. FTE: Possible. Number of Positions: 1. Schedule Hours: 8:30am-5pm, Monday-Friday.

Story Behind the Need

Global Artificial Intelligence & Machine Learning (GAIML) team is dedicated to creating innovative, intelligent software that drives value for the bank and its customers. We are a dynamic, multi-disciplinary team of Data Scientists, Software Engineers, and AI/ML Product Managers, committed to understanding global business challenges and transforming insights into impactful software solutions.

We are looking for a highly skilled and bilingual Data Scientist to join our team and contribute to the development of Large Language Models (LLM) and Generative AI (GenAI) solutions for the bank. In this role, you will work closely with internal business lines, data stewards and other internal stakeholders to drive business value, and recommend solutions to drive operational efficiency, revenue growth, cost reduction, product activation and usage. You will collaborate closely with Data Scientists to conduct thorough analytics and present insights and findings in a clear, impactful, and easily understandable manner for business partners and senior management.

Candidate Value Proposition

The successful candidate will have the opportunity to work on a high-visibility project, working closely with multiple departments, including an international team.

Typical Day in Role

• Assess and enhance the French version of the (RAG) system.
• Analyze large, complex multi-dimensional datasets in structured and unstructured format.
• Provide support to various partners and stakeholders across the bank by leading in the discovery process to identify business requirements and expected outcomes.
• Develop innovative and effective approaches and apply statistical, predictive modelling techniques to solve client’s analytics problems and communicate results and methodologies to business clients and senior members of the analytics team.
• Prepare detailed documentation to outline data sources, models and algorithms used and developed.
• Present and depict the rationale of findings in easy-to-understand terms for the business or senior management.
• Stay current on trends in the data science and fin-tech product space, translating those trends into actionable strategic and tactical objectives for the Bank.
• Contribute to a culture of innovation inside and outside of the company as a visionary capable of inspiring through presentation, demonstration and leading by example.

Candidate Requirements / Must Have Skills

1. Bilingual proficiency in English and French
2. 1-2 years of experience with Natural Language Processing (NLP), Large Language Models (LLM), and Retrieval Augmented Generation (RAG).
3. 1-2 years of hands-on experience with Python (Pandas, Scikit-Learn, NumPy, etc) and SQL (SQL Server, PostgreSQL, BigQuery, etc).
4. 1-2 years of experience with Cloud and Big Data ecosystem tools (GCP, Vertex AI, WorkStations, Docker, AirFlow, etc).
5. 1-2 years of experience with data engineering and data pipeline skills, with the ability to understand how to efficiently build model pipelines to support production ready models.

Nice-To-Have Skills

• Strong foundation in data mining and data cleaning to analyze large amounts of structured (Parquet, CSV, etc) and unstructured (XML, JSON, etc) data in a data lake environment and translating data into clear and concise findings.
• An excellent understanding and hands-on experience of Predictive Analytics and Machine Learning techniques like transformers, NLP, clustering and other similar techniques.
• Exposure to version control systems (e.g. Git)
• Knowledge of Bank Information Systems, such as product and reporting systems, including finance systems, Salesforce, GDAP, and the Enterprise Data Lake is an asset.
• Knowledge of Banking products and services is an asset.

Soft Skills

• Excellent verbal and written communication and interpersonal skills, with strong ability to present recommendations in a client-facing setting
• Collaborative skills
• A team player

Best vs Average

The ideal candidate would have experience with RAG and is bilingual English French. (Candidate will assess and enhance the French version of (RAG) system.)

Degrees or certifications

Post-secondary education in STEM disciplines (Computer Science, Electrical/Computer/Software Engineering or Mathematics); master’s degree preferred.

Candidate Review & Selection

• 2 Rounds
  • 1 round with Technical Team - 60 Mins – MS Teams Calls – Technical interview (RAG) and will be in French. Previous experience and role overview.
• 2nd round
  • Video call – Hiring manager and/or VP– 30 mins – Behavioral questions, previous experience questions and role fit.