What Data Scientist Jobs are in Edmonton?

• Lead the design, development, and deployment of advanced machine learning models and AI solutions.
• Conduct in-depth data analysis, identify patterns, and extract actionable insights from large, complex datasets.
• Develop and implement algorithms for predictive modeling, natural language processing, computer vision, and other AI applications.
• Collaborate with engineering and product teams to integrate ML models into production systems and applications.
• Mentor junior data scientists and engineers, providing technical guidance and fostering best practices in ML development.
• Define research directions and explore new techniques and technologies in AI/ML.
• Evaluate and select appropriate tools and platforms for data science and machine learning tasks.
• Communicate complex technical findings and recommendations to both technical and non-technical stakeholders.
• Ensure the ethical and responsible development and deployment of AI systems.
• Stay current with the latest research and advancements in the field of AI and Machine Learning.

• PhD or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field with a specialization in Machine Learning or Artificial Intelligence.
• 5+ years of hands-on experience in data science and machine learning, with a proven track record of leading AI projects.
• Strong expertise in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop).
• Solid understanding of statistical modeling, experimental design, and data mining techniques.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their ML services.
• Excellent problem-solving skills and the ability to translate business problems into data science solutions.
• Strong communication and presentation skills, with the ability to explain complex concepts clearly.
• Demonstrated ability to work independently and collaboratively in a remote environment.
• Experience with MLOps and model deployment pipelines is a plus.

• Highly competitive salary and bonus structure.
• Comprehensive health, dental, and vision coverage.
• Generous stock options and long-term incentives.
• Significant professional development budget for conferences, courses, and certifications.
• Flexible remote work schedule and home office stipend.
• Access to state-of-the-art computing resources and datasets.
• Opportunity to work on impactful AI projects with a talented and passionate team.
• A culture that values innovation, continuous learning, and work-life balance.

Our client, a dynamic startup revolutionizing the energy sector with predictive analytics, is seeking a Lead Data Scientist specializing in Machine Learning. This key role will drive the development and implementation of advanced ML models to forecast energy consumption, optimize grid performance, and identify efficiency opportunities. You will lead a team of data scientists and collaborate closely with engineers and domain experts to translate complex data into actionable insights. The ideal candidate possesses a strong academic background, extensive hands-on experience in machine learning, and proven leadership capabilities. This position offers a unique opportunity to shape the data science function and make a tangible impact in **Edmonton, Alberta, CA**.

• Lead the design, development, and deployment of machine learning models for applications such as forecasting, anomaly detection, and optimization.
• Mentor and guide junior data scientists, fostering a collaborative and innovative team environment.
• Collaborate with stakeholders across engineering, product, and business units to understand their needs and translate them into data science solutions.
• Develop and implement best practices for data collection, preprocessing, feature engineering, and model evaluation.
• Conduct rigorous statistical analysis and hypothesis testing to validate model performance and identify key drivers.
• Stay abreast of the latest research and advancements in machine learning and artificial intelligence, applying them to solve business problems.
• Communicate complex findings and recommendations clearly and effectively to both technical and non-technical audiences.
• Contribute to the company's data strategy and roadmap.
• Ensure the ethical and responsible use of data and AI within the organization.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of hands-on experience in data science and machine learning, with a focus on building and deploying ML models in production.
• Proven experience leading a team of data scientists or ML engineers.
• Strong proficiency in Python or R, and deep knowledge of ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Expertise in statistical modeling, time series analysis, and various ML algorithms (e.g., regression, classification, clustering, deep learning).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to convey technical concepts to diverse audiences.
• Experience in the energy sector or working with time-series data is a plus.
• This role is based in **Edmonton, Alberta, CA** and requires hybrid attendance.

Our client offers a competitive salary, performance bonuses, comprehensive health and dental coverage, a retirement savings program, and generous paid time off. Opportunities for professional development, conference attendance, and further education are provided. You will work in a modern, collaborative office environment in **Edmonton, Alberta, CA**, with the flexibility of a hybrid work arrangement.

• Develop and implement advanced statistical and machine learning models to solve business problems.
• Perform data exploration, cleaning, and feature engineering on large, complex datasets.
• Design and conduct experiments to test hypotheses and validate models.
• Build predictive models for forecasting, classification, clustering, and anomaly detection.
• Collaborate with business stakeholders to understand their needs and translate them into data science requirements.
• Communicate complex findings and recommendations clearly and concisely through visualizations and presentations.
• Develop and maintain data pipelines and analytical frameworks.
• Stay current with the latest advancements in data science, machine learning, and AI techniques.
• Mentor junior data scientists and contribute to the team's technical growth.
• Ensure the quality, integrity, and reproducibility of data science work.

• Master's degree or Ph.D. in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
• Minimum of 6 years of professional experience in data science or a related analytical role.
• Proven expertise in statistical modeling, machine learning algorithms, and data mining techniques.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Experience with SQL and working with large relational databases.
• Strong data visualization skills using tools like Matplotlib, Seaborn, Tableau, or Power BI.
• Excellent analytical, problem-solving, and critical thinking abilities.
• Strong communication and interpersonal skills, with the ability to explain technical concepts to diverse audiences.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data science services is beneficial.
• Knowledge of the **Alberta** business environment and industry trends is an advantage.

• Design, develop, and implement advanced statistical and machine learning models for financial applications (e.g., credit scoring, fraud detection, predictive analytics).
• Extract, clean, and transform large, complex datasets from various sources.
• Evaluate model performance, iterate on model development, and deploy models into production environments.
• Collaborate with product managers, engineers, and business stakeholders to understand data needs and translate them into analytical solutions.
• Conduct exploratory data analysis to uncover trends, patterns, and insights relevant to financial performance.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Develop robust data pipelines and feature engineering strategies.
• Communicate complex findings and recommendations clearly to both technical and non-technical audiences.
• Mentor junior data scientists and contribute to the team's technical knowledge base.

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Minimum of 5 years of experience as a Data Scientist, with a strong focus on financial modeling.
• Proven experience in developing and deploying machine learning models in a production environment.
• Proficiency in programming languages such as Python (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL.
• Strong understanding of statistical modeling, hypothesis testing, experimental design, and various machine learning algorithms.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills, comfortable working in a remote team environment.
• Familiarity with financial services regulations and data privacy is advantageous.

• Highly competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance plans.
• Generous paid time off and holidays.
• Retirement savings plan with employer matching.
• Significant opportunities for professional growth, continuous learning, and attending conferences.
• Flexible remote work environment.
• Work on cutting-edge projects in the dynamic fintech industry.

• Develop, test, and deploy predictive models using machine learning algorithms and statistical methods.
• Analyze large and complex datasets to identify trends, patterns, and insights relevant to business objectives.
• Clean, transform, and prepare data for modeling and analysis.
• Evaluate model performance and implement improvements to enhance accuracy and efficiency.
• Collaborate with data engineers to build and maintain data pipelines and infrastructure.
• Communicate findings and recommendations clearly to both technical and non-technical stakeholders through reports and presentations.
• Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence.
• Contribute to the development of data-driven strategies and solutions.
• Mentor junior analysts and contribute to the team's knowledge base.
• Ensure data quality and integrity throughout the analytical process.

• Master's or Ph.D. in Statistics, Data Science, Computer Science, Mathematics, Economics, or a related quantitative field.
• Minimum of 3 years of professional experience as a Data Scientist or in a similar analytical role.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow/PyTorch).
• Strong knowledge of statistical modeling, machine learning algorithms, and predictive analytics techniques.
• Experience with SQL and working with relational databases.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills.
• Ability to work effectively in a hybrid team environment.

• Competitive salary and bonus structure.
• Comprehensive health, dental, and vision benefits.
• Retirement savings plan with employer matching.
• Opportunities for professional development, training, and conference attendance.
• Flexible hybrid work arrangement.
• Access to advanced analytical tools and platforms.
• A collaborative and innovative work culture.

• Develop, validate, and deploy sophisticated machine learning models to address complex business challenges.
• Conduct exploratory data analysis to uncover trends, patterns, and insights from large datasets.
• Design and execute A/B tests and other experiments to evaluate model performance and product impact.
• Collaborate with engineering teams to integrate ML models into production systems and applications.
• Communicate findings, insights, and recommendations clearly to both technical and non-technical stakeholders through visualizations and presentations.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Mentor junior data scientists and contribute to the team's technical knowledge base.
• Identify opportunities for leveraging data and AI to improve products and business processes.
• Ensure data quality and integrity throughout the analytical process.
• Contribute to the development of data science best practices and standards within the organization.

• Master's or PhD in Computer Science, Statistics, Mathematics, Physics, Economics, or a related quantitative field.
• Minimum of 5 years of professional experience in data science or machine learning, with a proven track record of developing and deploying models.
• Strong proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Deep understanding of various machine learning algorithms (supervised, unsupervised, deep learning) and statistical modeling techniques.
• Experience with SQL and working with large relational databases.
• Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and interpersonal skills, with the ability to explain complex concepts simply.
• Ability to work effectively in a hybrid work environment, managing time and tasks efficiently.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).

• Competitive annual salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and company holidays.
• Stock options and equity incentives.
• Professional development opportunities, including training and conference attendance.
• Retirement savings plan with employer matching.
• A dynamic and collaborative work environment.
• Flexible hybrid work schedule.
• Employee assistance program.
• On-site parking and modern office facilities.

Our client, a prominent analytics firm, is seeking a highly skilled and analytical Data Scientist to join their team in Edmonton, Alberta . This hybrid role allows for a balance between in-office collaboration and remote work flexibility. The Data Scientist will be instrumental in extracting valuable insights from complex datasets, developing predictive models, and driving data-informed decision-making across the organization. You will work with cutting-edge tools and technologies to solve challenging business problems. The ideal candidate possesses a strong foundation in statistics, machine learning, and programming, coupled with the ability to communicate technical findings effectively to non-technical stakeholders. This position offers a fantastic opportunity to contribute to impactful projects and grow your career in a dynamic environment.

• Analyze large, complex datasets to identify trends, patterns, and actionable insights.
• Develop, train, and deploy machine learning models for prediction, classification, and clustering.
• Design and implement A/B tests and other experiments to evaluate model performance and business impact.
• Collaborate with business stakeholders to understand their needs and translate them into data science problems.
• Communicate complex findings and recommendations clearly and concisely to technical and non-technical audiences.
• Build data visualizations and dashboards to present insights effectively.
• Stay up-to-date with the latest advancements in data science, machine learning, and AI.
• Clean, transform, and preprocess data from various sources.
• Develop and maintain documentation for models, methodologies, and processes.
• Work with engineering teams to integrate data science solutions into production systems.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 5 years of professional experience as a Data Scientist or in a similar role.
• Strong proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with SQL and database querying.
• Solid understanding of statistical modeling, machine learning algorithms, and experimental design.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with data visualization tools (e.g., Tableau, Matplotlib, Seaborn).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills.
• Ability to work effectively both independently and as part of a collaborative team.

Our client offers a competitive salary, performance bonuses, and a comprehensive benefits package including health, dental, and vision insurance. The hybrid work model provides flexibility, and opportunities for professional development, including conferences and training, are readily available. You will work with a talented team on challenging and impactful projects, contributing to significant business outcomes. Enjoy a collaborative work environment with opportunities for career advancement within a growing organization.

• Define the product vision, strategy, and roadmap for generative AI products, aligning with company goals.
• Conduct market research, competitive analysis, and customer interviews to identify product opportunities and validate requirements.
• Translate complex AI concepts and user needs into detailed product specifications and user stories.
• Prioritize product backlog and manage the development lifecycle from ideation through launch and iteration.
• Collaborate closely with AI research scientists and engineers to ensure technical feasibility and innovation.
• Work with design and UX teams to create intuitive and engaging user experiences.
• Develop go-to-market strategies and collaborate with marketing and sales teams for product launches.
• Monitor product performance, gather user feedback, and drive continuous product improvement.
• Stay abreast of the latest advancements and trends in generative AI and the broader AI landscape.

• Bachelor's or Master's degree in Computer Science, Engineering, Business, or a related field.
• Minimum of 5 years of experience in product management, with at least 2 years focused on AI/ML products.
• Demonstrated experience with generative AI technologies, including LLMs, diffusion models, or similar.
• Proven ability to define product strategy, develop roadmaps, and manage product lifecycles.
• Strong understanding of AI/ML concepts and development processes.
• Excellent analytical, problem-solving, and strategic thinking skills.
• Exceptional communication, presentation, and interpersonal skills, with the ability to influence cross-functional teams.
• Experience working in a remote or hybrid work environment is beneficial.
• Familiarity with the **Edmonton, Alberta** tech ecosystem is a plus.

• Competitive salary package and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Stock options or other equity incentives.
• Generous budget for professional development and conferences.
• Flexible remote work policy.
• Opportunity to work with cutting-edge generative AI technologies.
• 401k or equivalent retirement savings plan.

• Deploy and manage machine learning models in cloud-based production environments (AWS, Azure, GCP).
• Develop and maintain MLOps pipelines for automated model training, validation, and deployment.
• Monitor the performance and health of deployed AI models and infrastructure.
• Troubleshoot and resolve issues related to model performance, scalability, and reliability.
• Collaborate with data scientists to optimize models for production readiness.
• Implement infrastructure as code (IaC) for managing AI/ML environments.
• Optimize model inference speed and resource utilization.
• Develop tools and scripts to automate AI/ML workflows.
• Stay current with emerging trends and best practices in MLOps and AI deployment.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 3 years of experience in software engineering, data engineering, or ML engineering.
• Proven experience deploying and managing machine learning models in production.
• Strong understanding of ML concepts and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their AI/ML services.
• Familiarity with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow).
• Proficiency in scripting languages such as Python.
• Experience with CI/CD pipelines and infrastructure automation.
• Excellent problem-solving and debugging skills.
• Strong communication skills for effective remote collaboration.

• Competitive salary and performance bonus.
• Comprehensive health, dental, and vision insurance.
• Flexible remote work environment with adjustable hours.
• Opportunities for professional development and learning new AI technologies.
• Contribute to innovative AI solutions that drive business value.
• Collaborative and supportive team culture.
• Generous paid time off.