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Big Data Scientist Jobs in Toronto

1 - 15 of 28
1 - 15 of 28
Search Results - Big Data Scientist Jobs in Toronto
Capgemini-Toronto
efficient data structures and algorithms for big data processing. Distributed Systems: Experience with distributed computing frameworks and parallel processing. Data Integration: Proficiency in integrating data from various sources and ensuring data...
Rackspace-Toronto
The best part is, we’re committed to you and your growth, both professionally and personally. Overview As a Big Data Architect, you are passionate about data and technology solutions, are driven to learn about them and keep up with market evolution. You...
appcast.io -
Magna International-Toronto
is desired and basic AI fundamentals Familiarity with big data technologies (e.g., Spark, Kafka) and cloud platforms (AWS, GCP, Azure). Familiarity with edge computing, real-time data processing, and digital twin. Strong problem-solving abilities...
HRB-Toronto
Who are we? We apply big data, artificial intelligence, and machine learning to bring the next generation of financial products and services to global markets. Position Summary: We are seeking a Data Scientist to develop large-scale big-data...
appcast.io -
Definity Financial Corporation-Toronto
such as databases and large-scale processing systems. They will work closely with data scientists and analysts to understand the organization's data needs and help design solutions. Qualifications  •  Experience with big data technologies like Hadoop, Spark...
TD Bank-Toronto
actionable insights or build analytics solutions that guide decision making and strategic planning. In addition, Lead Data Scientists provide oversight and consultative advice and guidance to others as the lead or top Data Scientist with enterprise...
appcast.io -
Apexon-Toronto
Familiarity with Python data science libraries such as Pandas, NumPy, and Scikit-learn for data manipulation, analysis, and modeling.  •  Knowledge of database systems and SQL for data retrieval, manipulation, and storage.  •  Understanding of big data...
Essex Lake Group-Toronto
Big Data, Advanced Analytics and its extensive executive and industry experience. Essex’ customized battle-tested solutions deliver a measurable positive impact within 6 to 18 months. Essex solutions have created substantial profit increases...
Essex Lake Group-Toronto
under the guidance of SI Managers and Client Initiative Leaders. SI Analysts II are highly proficient in big-data analytical tools such as SQL, SAS, Python or R and are experienced in manipulating granular transactional or customer-level data . They help...
Apexon-Toronto
Familiarity with Python data science libraries such as Pandas, NumPy, and Scikit-learn for data manipulation, analysis, and modeling.  •  Knowledge of database systems and SQL for data retrieval, manipulation, and storage.  •  Understanding of big data...
CGI Group-Toronto
opportunities, help shortlist and turn those opportunities into action, and then scale it across the organization unlocking a larger impact for clients and their consumers. For this, we depend on a talented and motivated team of Data Architects, Data Scientists...
Definity Financial Corporation-Toronto
such as databases and large-scale processing systems. They will work closely with data scientists and analysts to understand the organization's data needs and help design solutions. Qualifications  •  Experience with big data technologies like Hadoop, Spark...
CGI Group-Toronto
opportunities, help shortlist and turn those opportunities into action, and then scale it across the organization unlocking a larger impact for clients and their consumers. For this, we depend on a talented and motivated team of Data Architects, Data Scientists...
Royal Bank of Canada-Toronto
Job Summary Explores and operationalizes big data sources using scientific processes and technologies to uncover and communicate product and business insights. Applies experience and seasoned knowledge, skills, and practices to perform a variety...
rbc.com -
Deloitte-Toronto
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver efficient solutions. Optimize and tune Spark applications for performance and scalability. Implement best practices for data engineering, including...
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