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.

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