Top Data Science Jobs in Vancouver
Sun Life is seeking a Data Scientist to join their team and empower individuals, families, and communities worldwide. The Data Scientist will work on innovative technology, financial services, and asset management solutions to support clients in achieving lifetime financial security and living healthier lives.
Data Engineers at Credera work closely with Subject Matter Experts to design the ontology, develop data pipelines, and integrate Foundry with external systems. Responsibilities include project work with Palantir Foundry, Python expertise, machine learning, and collaboration with Product teams. Requirements include proficiency in Python, PySpark, SQL, AWS, Git, and agile working methodology.
Rill Data is seeking a Data Engineering Lead who will have a direct impact on Rill and its customers by implementing the data infrastructure, leading a team of data engineers, and driving implementations of customer data pipelines. The ideal candidate will have experience in designing and managing enterprise-level database systems, working with high volume and high velocity data, and using tools like Python, Scala, SQL, Apache Flink, Apache Beam, Apache Spark, DBT, Airflow, Snowflake, BigQuery, Redshift, HIVE, and Apache Kafka.
Seeking an experienced Data Engineer to architect and develop data pipelines, collaborate with clients, design cloud-based data platforms, implement data governance best practices, build data models, and work on comprehensive data solutions. Must have 5+ years of experience in data engineering, expertise in cloud data services, and familiarity with BI tools and programming skills in Python.
Boeing Vancouver is seeking a Senior Data Engineer to design and build a data sharing platform through distributed, decentralized ownership using the data mesh architectural pattern. Responsibilities include designing and implementing data pipelines, defining data models, ensuring data quality, and providing technical leadership in data processing and governance.
Join Super.com as a Senior Analytics Engineer to evolve the foundational data infrastructure supporting the finance department. Lead data projects, promote a data-driven culture, and collaborate with key stakeholders to advance analytics strategy. Ideal candidate has 3+ years of experience, strong SQL skills, data modelling expertise, and a track record of project delivery.
Automate manual processes through SQL and Python, design ETL solutions, analyze and extract data, create data visualizations, work with Google Analytics, and manage data infrastructure. Bachelor's or Master's degree in relevant field required. Must have 2-4 years of experience in digital marketing analytics.
Seeking a Staff Data Engineer to lead data engineering initiatives and build analytical solutions. Responsibilities include designing data pipelines, managing data infrastructure, ensuring data quality, and mentoring team members. Requires 8+ years of experience in data engineering and expertise in Snowflake, ETL/ELT, AWS, Python, and DevOps tools.
The Data Science Engineer at Coalition is responsible for owning and maintaining robust data models, collaborating with various teams, improving the analytics data stack efficiency, mentoring junior employees, and more. The role requires expertise in SQL, Python, R, data modeling, analytics tools, and strong communication skills.
Seeking a seasoned Staff Data Engineer to lead data engineering initiatives and build end-to-end analytical solutions using modern cloud technologies. Responsibilities include designing and managing data pipelines, ensuring data quality, building new data models, and mentoring team members. Ideal candidates will have extensive experience in data engineering and technologies such as Snowflake, ETL/ELT, AWS, and Python scripting.
The Senior Data Engineer at GeoComply constructs data pipelines to transform raw data into actionable business insights, supporting both the company and customers in decision-making processes. Responsibilities include developing and maintaining data pipelines, generating automated reports, and coordinating with the Engineering team on release cycles.
Lead the design and development of a robust data architecture, serve as a data and analytics solution architect, establish standards for data modeling and integration, work on batch and real-time streaming infrastructure, collaborate with cross-functional teams to design data solutions, and improve customer satisfaction for internal customers.
Seeking an enthusiastic Entry-Level Data Engineer with a focus on AI to assist in designing, building, and maintaining data infrastructure that supports artificial intelligence and machine learning initiatives. Responsibilities include data pipeline development, data integration, AI & ML support, data monitoring, and troubleshooting. Preferred skills include practical knowledge of programming languages, SQL, AI frameworks, big data technologies, cloud platforms, data modeling, and strong analytical skills.
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Join StackAdapt as a Senior Data Scientist focusing on building models to predict and optimize internal business operations, customer acquisition, and revenue forecasting. Collaborate with internal teams to solve business problems through data science.
As a Senior Data Engineer at Viral Nation, you will design and maintain robust data pipelines, implement efficient data models, integrate data from various sources, optimize performance, enforce data governance, and collaborate with cross-functional teams.
Seeking a Data Scientist with expertise in SQL, Python, GCP, and Data Science, focusing on NLP. Responsibilities include complex data analysis, data pipeline management, model development, and providing actionable insights. Preferred qualifications include experience in the travel industry and familiarity with revenue management models.
As a Data Engineer at Walmart, you will be responsible for developing and maintaining data pipelines to support data science initiatives. You will work with a mammoth scale of data to create valuable data assets for retail analytics. Collaboration with Data Scientists, Analysts, and business stakeholders to solve complex challenges is crucial for evolving the retail business model.
Lead large-scale data projects, solve complex problems, deliver results that impact business, engage with stakeholders, mitigate risks, and mentor team members. Must have advanced degree in quantitative field and experience in data science.
Join Figment as a Senior Data Engineer to build and manage data pipelines, implement data modeling, and automate data processes. Collaborate with teams to improve data infrastructure and promote best practices in data engineering.
Seeking a Senior Analytics Engineer to lead the transformation layer of a data platform at a fast-growing fintech company. Responsibilities include developing scalable patterns, ensuring data discoverability, and collaborating with various teams. Must have 3+ years of experience in data engineering or analytics, expertise in SQL and Python, and strong relational database skills.
Lead Data Scientist / Applied Statistician with experience in sequential testing.
The Senior Data Scientist at Sensor Tower will leverage digital advertising knowledge to drive strategies for improving Digital Marketing insights solutions.
As a Senior Data Scientist at StreamElements, you will create innovative analytic and software solutions to solve business problems. Responsibilities include driving strategic projects, designing and executing multi-disciplinary data science solutions, partnering with business leaders, furthering technical capabilities, and promoting an inclusive environment within the team.
Join BCI as a Full Stack Data Engineer, responsible for designing, developing, and implementing end-to-end data and analytics solutions including data engineering, BI engineering, data science, and machine learning engineering. Work on data modernization, analytics solutions, and machine learning models. Requires 5 years of experience and proficiency in SQL, Power BI, Tableau, and Azure.
Building predictive and optimization models to guide company resourcing decisions, supporting company financial health, making data science modeling accessible to non-experts, and implementing forecasting algorithms for revenue planning. Collaborating with data engineers to implement ML algorithms in production.
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