Data Science Developer

Role: Data Science Developer Client: Government, Broader Public Sector Job Type: Contract Term: 12 Months Workplace Type: Hybrid / Onsite Pay Rate: Negotiable Start date: 2-3 weeks Location: Toronto, ON Language: English Clearance: N/A ATS ID : 9863 Requirements: What you'll need Skills, Knowledge, Experience, and Qualifications: Experience: 2–5 years of professional experience in data science, data analytics, or a related quantitative field (e.g., data engineering, machine learning, or business intelligence) or equivalent. Proven experience in data analysis, visualization, and statistical modeling for real-world business or research problems. Demonstrated ability to clean, transform, and manage large datasets using Python, R, or SQL. Hands-on experience building and deploying predictive models or machine learning solutions in production or business environments. Experience with data storytelling and communicating analytical insights to non-technical stakeholders. Exposure to cloud environments (AWS, Azure, or GCP) and version control tools (e.g., Git). Experience working in collaborative, cross-functional teams, ideally within Agile or iterative project structures. Knowledge of ETL pipelines, APIs, or automated data workflows is an asset. Previous work with dashboarding tools (Power BI, Tableau, or Looker) is preferred. Technical Skills: Programming & Data Handling Python (pandas, NumPy, scikit-learn, statsmodels, matplotlib, seaborn) SQL (complex queries, joins, aggregations, optimization) Data preprocessing (feature engineering, missing data handling, outlier detection) Machine Learning & Statistical Modeling Proficiency in supervised and unsupervised learning techniques (regression, classification, clustering, dimensionality reduction) Understanding of model evaluation metrics and validation techniques (cross-validation, A/B testing, ROC-AUC, confusion matrix) Basic understanding of deep learning frameworks (TensorFlow, PyTorch, or Keras) is a plus Data Visualization & Reporting Expertise with visualization libraries (matplotlib, seaborn, plotly, or equivalent) Experience building interactive dashboards (Tableau, Power BI, Dash, or Streamlit) Ability to design clear, impactful data narratives and reports Data Infrastructure & Tools Experience with cloud-based data services (e.g., AWS S3, Redshift, Azure Data Lake, GCP BigQuery) Experience working with big data frameworks such as Apache Spark and Hadoop for large-scale data processing. Familiarity with data pipeline and workflow tools Experience with API integration and data automation scripts (Selenium, Python, etc) Solid grounding in probability, statistics, and linear algebra Understanding of hypothesis testing, confidence intervals, and sampling methods Soft Skills: Strong communication skills; both written and verbal Ability to develop and present new ideas and conceptualize new approaches and solutions Excellent interpersonal relations and demonstrated ability to work with others effectively in teams Demonstrated ability to work with functional and technical teams Demonstrated ability to participate in a large team and work closely with other individual team members Proven analytical skills and systematic problem solving Strong ability to work under pressure, work with aggressive timelines, and be adaptive to change Displays problem-solving and analytical skills, using them to resolve technical problems Must Have: 2–5 years of professional experience in data science, data analytics, or a related quantitative field (e.g., data engineering, machine learning, or business intelligence) or equivalent. Proven experience in data analysis, visualization, and statistical modeling for real-world business or research problems. Demonstrated ability to clean, transform, and manage large datasets using Python, R, or SQL. Programming & Data Handling Python (pandas, NumPy, scikit-learn, statsmodels, matplotlib, seaborn) SQL (complex queries, joins, aggregations, optimization) Data preprocessing (feature engineering, missing data handling, outlier detection) Experience working with big data frameworks such as Apache Spark and Hadoop for large-scale data processing. PREFERRED SKILLS Data Science Data Analysis Python SQL Apache Spark or Hadoop Selenium Azure or GCP HOW TO APPLY Patrick Marsan is hiring for this position. Apply through LinkedIn. Follow Wirehead on LinkedIn Interested in working with us in the future? members who follow a company they’re interested in, like Wirehead, are 5x more likely to receive a message from a recruiter than those who don’t. We thank all candidates for their interest but advise that only candidates selected for interviews will be contacted. Rest assured that your resume will be kept on our database and will be considered for all future opportunities. Applicants must be authorized to work in Canada. Copyright 2007 - 2025 | Wirehead Talent | All rights reserved

Location: Toronto, Ontario, CA

Posted Date: 11/18/2025