- 经验
- 5年以上
- 薪水
- —
- 职位空缺
- 1
- 发布
- 4小时前
- 工作模式
- 在办公室
- 学历
- Bachelor's degree in STEM or equivalent experience
- 恢复
- 需要申请
你的工作地点
职位描述
Role Overview
This position is for a Data Scientist based in Mississauga, ON, requiring onsite presence three days per week on a contract basis.
Key Responsibilities
- Examine substantial structured and unstructured datasets to uncover trends, patterns, and valuable business insights.
- Perform tasks such as data cleansing, transformation, and feature engineering to facilitate model creation.
- Create, evaluate, and sustain both predictive and prescriptive models using statistical and machine learning approaches.
- Assist in deploying analytical solutions in production settings in collaboration with technology teams.
- Support the machine learning lifecycle including development, testing, training, monitoring, and performance assessment.
- Work jointly with business, technology, and risk stakeholders to gather requirements and convert them into analytical outputs.
- Maintain documentation covering methodologies, assumptions, and modeling outcomes to aid governance and assessment processes.
- Deliver presentations on analytical results and project progress to colleagues and stakeholders.
- Stay current with and apply advanced methods in Machine Learning, Deep Learning, Large Language Models (LLMs), and Generative AI.
Preferred Qualifications
- A minimum of five years in data science, machine learning, advanced analytics, or related disciplines.
- Experience in creating and assessing machine learning models.
- Familiarity with ML/DL concepts and the model development lifecycle.
- Proficiency in Python, SQL, Spark, PySpark, TensorFlow, or comparable analytic and modeling software.
- Knowledge of Large Language Models and Generative AI tools.
- Strong problem-solving, analytical capabilities, and effective communication skills.
- Capability to work autonomously while collaborating productively within cross-functional teams.
Additional Desired Skills
- Hands-on experience supporting ML, AI, or GenAI applications in production environments.
- Working knowledge of distributed computing frameworks such as Hadoop, Hive, Spark, or cloud analytics platforms.
- Background in banking, retail risk management, or financial services is advantageous.
- Basic familiarity with capital markets, financial instruments, and quantitative modeling.
Educational Requirements
A bachelor's or university degree in a STEM-related field is required, with advanced degrees preferred.