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Intermediate Data Science Developer

2 weeks ago

Toronto, Ontario, Canada CCI- Computer Consultants International, Inc. Full time $80,000 - $120,000 per year

Candidates MUST be authorized to work in Canada / hold a valid work visa. CCI does not sponsor work visas.

Responsibilities:

  • Participate in product teams to analyze systems requirements, architect, design, code and implement cloud-based data and analytics products that conform to standards.
  • Design, create, and maintain cloud-based data lake and lakehouse structures, automated data pipelines, analytics models, and visualizations (dashboards and reports).
  • Liaises with cluster IT colleagues to implement products, conduct reviews, resolve operational problems, and support business partners in effective use of cloud-based data and analytics products.
  • Analyses complex technical issues, identifies alternatives and recommends solutions. Prepare and conduct knowledge transfer

Mandatory Skills:

  • 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.

Experience and Skill Set Requirements (Evaluation criteria)

Experience - 40 %

  • 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 - 35%

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- 20%

  • 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

Public sector Experience- 5%

  • OPS(or other government) standards and processes