Develop and optimize predictive and prescriptive models to extract insights and enhance decision-making.
Apply deep learning and neural network techniques for customer classification, segmentation, and personalization.
Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production.
Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement.
Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations.
Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred).
Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently and implement CI/CD workflows to automate model training, deployment, and monitoring.
Collaborate in an Agile/DevOps environment, promoting a data-centric culture and clearly communicating complex methodologies and insights to technical and non-technical audiences.

Requirements

7+ years of experience in Data Science, Machine Learning, or related fields
Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring
Proficiency in cloud platforms (GCP/AWS) and scalable data engineering
Strong understanding of probability theory, statistics, and experimental design (A/B Testing)
Experience with collaborative software engineering practices (Agile, DevOps)
Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or related field
Preferred Qualifications: Experience with Knowledge Graphs and their integration into AI/ML pipelines; Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies; Background in Retail and Personalization Web Technologies; Understanding of digital ecosystems and data-driven decision-making; Proficiency in BI tools and data visualization.

Benefits

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

PythonSQLdeep learningneural networksMLOpsLarge Language ModelsGenerative AIETLA/B Testingdata visualization

collaborationcommunicationAgileDevOpsdata-centric culture

Bachelor’s degreeMaster’s degree