Data Scientist
Contractor
contractor
9 May 2024
Toronto
Verified by Turrior
Content + Source + Freshness • 12 Dec 2025 • 95% confidence
78 / 100
Offer value
Moderate value as the role demands extensive experience, particularly in niche areas of data science, amidst competitive market conditions.
- Extensive experience required (10+ years in data science)
- Strong engagement with advanced data analytics tools
- Intermediate work-life balance with expectations of fast-paced projects
Pros
- Engaging responsibilities involving advanced data analytics
- Collaboration with diverse teams enhances professional network
- chance to work with cutting-edge tools such as Power BI and Spark
Cons
- High experience requirement (10+ years) may limit candidate pool
- Intense workload could impact work-life balance
- Potentially rapid changes in data analytics trends requiring ongoing learning
Who it's for
Senior • Onsite
Good fit
- Experienced Data Scientists
- Professionals with solid backgrounds in statistics and machine learning
- Candidates interested in cross-functional collaboration
Not recommended for
- Entry-level applicants or less than 10 years of experience
- Individuals prioritizing remote work
- Candidates without practical experience in data analytics tools
Motivation fit
Interest in leveraging data to drive business valueEagerness to collaborate across departmentsMotivation to stay ahead in the evolving data landscape
Key skills
Data modeling and transformationStatistical analysis and machine learningCloud computing and big data technologiesEffective stakeholder communication
Score: 78/100 AI verified analysis
About the job
Typical Day in Role:
• Collaborate with business lines and other stakeholders and identify opportunities to drive business value by leveraging data science and data engineering solutions?
• Efficiently handle large volumes of structured and unstructured data through ingestion, modeling, transformation, and storage across diverse data stores. Leverage distributed computing tools (e.g., Spark, Cloud) for analysis, data mining, and modeling
• Collaborate with operation, and other analytics teams to deploy models and algorithms in production across different channels and platforms?
• Work with the team to design the project architecture and road map.
• Prepare detailed documentation to outline data sources, models, and algorithms used and developed.?
• Present results to business line stakeholders and help implement real world data-driven changes.
Candidate Requirements/Must Have Skills:
1) 10+ years of combined working experience with SQL, Spark and relational databases technologies/concepts for both
2) 10+ years of production experience with statistical analysis, machine learning and digital analytics (e.g., hypothesis driven analysis, acquisition, and fraud/anomaly detection)
3) 3-5+ years’ experience with Power BI and/or Tableau (Power BI preferable)
Nice-To-Have Skills:
1) Domain knowledge/experience with on digital authentication and digital fraud analytics.
2) Hands-on experience with Big Data/Cloud ecosystem (GCP)
3) Experience with existing Know-Your-Customer (KYC) practices across financial institutions and the supporting technologies
Soft Skills Required:
• Excellent written, verbal, and interpersonal skills for executive level communication and collaboration
• Able to work in a fast-paced, constantly evolving environment and manage multiple priorities.
• Pragmatic and capable of solving complex issues.
• Strong experience working with a variety of cross-functional teams.
Education:
Bachelor’s Degree or equivalent in in Computer Science, Engineering, or relevant field.
• Collaborate with business lines and other stakeholders and identify opportunities to drive business value by leveraging data science and data engineering solutions?
• Efficiently handle large volumes of structured and unstructured data through ingestion, modeling, transformation, and storage across diverse data stores. Leverage distributed computing tools (e.g., Spark, Cloud) for analysis, data mining, and modeling
• Collaborate with operation, and other analytics teams to deploy models and algorithms in production across different channels and platforms?
• Work with the team to design the project architecture and road map.
• Prepare detailed documentation to outline data sources, models, and algorithms used and developed.?
• Present results to business line stakeholders and help implement real world data-driven changes.
Candidate Requirements/Must Have Skills:
1) 10+ years of combined working experience with SQL, Spark and relational databases technologies/concepts for both
2) 10+ years of production experience with statistical analysis, machine learning and digital analytics (e.g., hypothesis driven analysis, acquisition, and fraud/anomaly detection)
3) 3-5+ years’ experience with Power BI and/or Tableau (Power BI preferable)
Nice-To-Have Skills:
1) Domain knowledge/experience with on digital authentication and digital fraud analytics.
2) Hands-on experience with Big Data/Cloud ecosystem (GCP)
3) Experience with existing Know-Your-Customer (KYC) practices across financial institutions and the supporting technologies
Soft Skills Required:
• Excellent written, verbal, and interpersonal skills for executive level communication and collaboration
• Able to work in a fast-paced, constantly evolving environment and manage multiple priorities.
• Pragmatic and capable of solving complex issues.
• Strong experience working with a variety of cross-functional teams.
Education:
Bachelor’s Degree or equivalent in in Computer Science, Engineering, or relevant field.
