Data Science Developer (Intermediate) 9863-3112

Toronto - Canada

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

HM Note: This hybrid contract role is five (5) days in office. Candidate resumes must include first and last name email and telephone contact information.

Description

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

General Skills:

Experience in multiple cloud base data and analytics platforms and coding/programming/scripting tools to create maintain support and operate cloud-based data and analytics products.
Experience with designing creating and maintaining cloud-based data lake and lakehouse structures automated data pipelines analytics models and visualizations (dashboards and reporting) in real world implementations
Experience in assessing client information technology needs and objectives
Experience in problem-solving to resolve complex multi-component failures
Experience in preparing knowledge transfer documentation and conducting knowledge transfer
A team player with a track record for meeting deadlines

Desirable Skills:

Written and oral communication skills to participate in team meetings write/edit systems documentation prepare and present written reports on findings/alternate solutions develop guidelines / best practices Interpersonal skills to explain and discuss advantages and disadvantages of various approaches
Experience in conducting knowledge transfer sessions and building documentation for technical staff related to architecting designing and implementing end to end data and analytics products Technology Stack Azure Storage Azure Data Lake Azure Databricks Lakehouse and Azure Synapse Python SQL Azure Databricks and Azure Data Factory Power BI

Skills

Experience and Skill Set Requirements

Experience - 40 % and nbsp;

25 years and nbsp;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 and nbsp;data analysis visualization and statistical modeling and nbsp;for real-world business or research problems.
Demonstrated ability to and nbsp;clean transform and manage large datasets and nbsp;using Python R or SQL.
Hands-on experience building and deploying and nbsp;predictive models or machine learning solutions and nbsp;in production or business environments.
Experience with and nbsp;data storytelling and nbsp;and communicating analytical insights to non-technical stakeholders.
Exposure to and nbsp;cloud environments and nbsp;(AWS Azure or GCP) and and nbsp;version control tools and nbsp;(e.g. Git).
Experience working in and nbsp;collaborative cross-functional teams ideally within Agile or iterative project structures.
Knowledge of and nbsp;ETL pipelines APIs or automated data workflows and nbsp;is an asset.
Previous work with and nbsp;dashboarding tools and nbsp;(Power BI Tableau or Looker) is preferred.

and nbsp; and nbsp;

Technical Skills - 35% and nbsp;

Programming and amp; Data Handling

Python and nbsp;(pandas NumPy scikit-learn statsmodels matplotlib seaborn)
SQL and nbsp;(complex queries joins aggregations optimization)
Data preprocessing and nbsp;(feature engineering missing data handling outlier detection)

Machine Learning and amp; Statistical Modeling

Proficiency in and nbsp;supervised and unsupervised learning and nbsp;techniques (regression classification clustering dimensionality reduction)
Understanding of and nbsp;model evaluation metrics and nbsp;and validation techniques (cross-validation A/B testing ROC-AUC confusion matrix)
Basic understanding of and nbsp;deep learning frameworks and nbsp;(TensorFlow PyTorch or Keras) is a plus

Data Visualization and amp; Reporting

Expertise with and nbsp;visualization libraries and nbsp;(matplotlib seaborn plotly or equivalent)
Experience building interactive and nbsp;dashboards and nbsp;(Tableau Power BI Dash or Streamlit)
Ability to design and nbsp;clear impactful data narratives and reports

Data Infrastructure and amp; Tools

Experience with and nbsp;cloud-based data services and nbsp;(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 and nbsp;data pipeline and workflow tools
Experience with and nbsp;API integration and nbsp;and and nbsp;data automation scripts (Selenium Python etc)
Solid grounding in and nbsp;probability statistics and linear algebra
Understanding of and nbsp;hypothesis testing confidence intervals and sampling methods

Soft Skills- 20% and nbsp;

Strong communication skills; both written and verbal and nbsp;
Ability to develop and present new ideas and conceptualize new approaches and solutions and nbsp;
Excellent interpersonal relations and demonstrated ability to work with others effectively in teams and nbsp;
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 and nbsp;
Proven analytical skills and systematic problem solving and nbsp;
Strong ability to work under pressure work with aggressive timelines and be adaptive to change and nbsp;
Displays problem-solving and analytical skills using them to resolve technical problems and nbsp;

and nbsp; and nbsp;

Public sector Experience- 5% and nbsp;

OPS(or other government) standards and processes

Must Have:

25 years and nbsp;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 and nbsp;data analysis visualization and statistical modeling and nbsp;for real-world business or research problems.
Demonstrated ability to and nbsp;clean transform and manage large datasets and nbsp;using Python R or SQL.
Programming and amp; Data Handling

Python and nbsp;(pandas NumPy scikit-learn statsmodels matplotlib seaborn)
SQL and nbsp;(complex queries joins aggregations optimization)
Data preprocessing and nbsp;(feature engineering missing data handling outlier detection)

Experience working with big data frameworks such as Apache Spark and Hadoop for large-scale data processing.

HM Note: This hybrid contract role is five (5) days in office. Candidate resumes must include first and last name email and telephone contact information.DescriptionResponsibilities:Participate in product teams to analyze systems requirements architect design code and implement cloud-based data and ...

HM Note: This hybrid contract role is five (5) days in office. Candidate resumes must include first and last name email and telephone contact information.

Description

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

General Skills:

Experience in multiple cloud base data and analytics platforms and coding/programming/scripting tools to create maintain support and operate cloud-based data and analytics products.
Experience with designing creating and maintaining cloud-based data lake and lakehouse structures automated data pipelines analytics models and visualizations (dashboards and reporting) in real world implementations
Experience in assessing client information technology needs and objectives
Experience in problem-solving to resolve complex multi-component failures
Experience in preparing knowledge transfer documentation and conducting knowledge transfer
A team player with a track record for meeting deadlines

Desirable Skills:

Written and oral communication skills to participate in team meetings write/edit systems documentation prepare and present written reports on findings/alternate solutions develop guidelines / best practices Interpersonal skills to explain and discuss advantages and disadvantages of various approaches
Experience in conducting knowledge transfer sessions and building documentation for technical staff related to architecting designing and implementing end to end data and analytics products Technology Stack Azure Storage Azure Data Lake Azure Databricks Lakehouse and Azure Synapse Python SQL Azure Databricks and Azure Data Factory Power BI

Skills

Experience and Skill Set Requirements

Experience - 40 % and nbsp;

25 years and nbsp;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 and nbsp;data analysis visualization and statistical modeling and nbsp;for real-world business or research problems.
Demonstrated ability to and nbsp;clean transform and manage large datasets and nbsp;using Python R or SQL.
Hands-on experience building and deploying and nbsp;predictive models or machine learning solutions and nbsp;in production or business environments.
Experience with and nbsp;data storytelling and nbsp;and communicating analytical insights to non-technical stakeholders.
Exposure to and nbsp;cloud environments and nbsp;(AWS Azure or GCP) and and nbsp;version control tools and nbsp;(e.g. Git).
Experience working in and nbsp;collaborative cross-functional teams ideally within Agile or iterative project structures.
Knowledge of and nbsp;ETL pipelines APIs or automated data workflows and nbsp;is an asset.
Previous work with and nbsp;dashboarding tools and nbsp;(Power BI Tableau or Looker) is preferred.

and nbsp; and nbsp;

Technical Skills - 35% and nbsp;

Programming and amp; Data Handling

Python and nbsp;(pandas NumPy scikit-learn statsmodels matplotlib seaborn)
SQL and nbsp;(complex queries joins aggregations optimization)
Data preprocessing and nbsp;(feature engineering missing data handling outlier detection)

Machine Learning and amp; Statistical Modeling

Proficiency in and nbsp;supervised and unsupervised learning and nbsp;techniques (regression classification clustering dimensionality reduction)
Understanding of and nbsp;model evaluation metrics and nbsp;and validation techniques (cross-validation A/B testing ROC-AUC confusion matrix)
Basic understanding of and nbsp;deep learning frameworks and nbsp;(TensorFlow PyTorch or Keras) is a plus

Data Visualization and amp; Reporting

Expertise with and nbsp;visualization libraries and nbsp;(matplotlib seaborn plotly or equivalent)
Experience building interactive and nbsp;dashboards and nbsp;(Tableau Power BI Dash or Streamlit)
Ability to design and nbsp;clear impactful data narratives and reports

Data Infrastructure and amp; Tools

Experience with and nbsp;cloud-based data services and nbsp;(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 and nbsp;data pipeline and workflow tools
Experience with and nbsp;API integration and nbsp;and and nbsp;data automation scripts (Selenium Python etc)
Solid grounding in and nbsp;probability statistics and linear algebra
Understanding of and nbsp;hypothesis testing confidence intervals and sampling methods

Soft Skills- 20% and nbsp;

Strong communication skills; both written and verbal and nbsp;
Ability to develop and present new ideas and conceptualize new approaches and solutions and nbsp;
Excellent interpersonal relations and demonstrated ability to work with others effectively in teams and nbsp;
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 and nbsp;
Proven analytical skills and systematic problem solving and nbsp;
Strong ability to work under pressure work with aggressive timelines and be adaptive to change and nbsp;
Displays problem-solving and analytical skills using them to resolve technical problems and nbsp;

and nbsp; and nbsp;

Public sector Experience- 5% and nbsp;

OPS(or other government) standards and processes

Must Have:

25 years and nbsp;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 and nbsp;data analysis visualization and statistical modeling and nbsp;for real-world business or research problems.
Demonstrated ability to and nbsp;clean transform and manage large datasets and nbsp;using Python R or SQL.
Programming and amp; Data Handling

Python and nbsp;(pandas NumPy scikit-learn statsmodels matplotlib seaborn)
SQL and nbsp;(complex queries joins aggregations optimization)
Data preprocessing and nbsp;(feature engineering missing data handling outlier detection)