Senior Data Scientist
Come Work with Us!
At RBC, our culture is deeply supportive and rich in opportunity and reward. You will help our clients thrive and our communities prosper, empowered by a spirit of shared purpose.
Whether you’re helping clients find new opportunities, developing new technology, or providing expert advice to internal partners, you will be doing work that matters in the world, in an environment built on teamwork, service, responsibility, diversity, and integrity.
Senior Data Scientist
AIOPS (AI for IT Operations) Senior Data Scientist
WHAT IS THE OPPORTUNITY?
RBC Technology Infrastructure seeks a full stack Data Scientist (DS) to explore and operationalize big data sources to reduce outage and down time for RBC services that leads to improve user experience and save costs. Seeking a DS with experience in applied research and problem solving to join our team. The successful candidate will have experience with developing and deploying production grade AI/ML solutions, have broad expertise in statistics, analytics, ML and strong programming skill.
WHAT WILL YOU DO?
- Lead full life-cycle Data Science solutions from beginning to model deployment and monitoring and partner with the engineering team to ensure best practices for ML model deployment.
- Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
- Experience in (Python, R, Scala, SQL, NoSQL, etc.) to obtain, integrate, manipulate, and analyze data from multiple sources.
- Expertise in statistical data analysis (e.g. univariate/bivariate analysis) and data quality assessment.
- Build Machine Learning, Deep Learning and statistical models to solve specific business problems.
- Developing predictive data models, anomaly detection model, quantitative analyses and visualization of targeted big data sources.
- Leading data exploration and analytic projects and providing on-going coaching of big data topics (visualization, data mining, analytic techniques).
- Exploring and implementing semantic data capabilities through NLP, text mining and machine learning techniques.
- Overseeing the acquisitions and ingestions of data from structured and unstructured sources, while ensuring quality and comprehensiveness of data.
- Utilizing APIs to collect data from various products into the Data Warehouse Database.
WHAT DO YOU NEED TO SUCCEED?
- 5+ years of industry experience required working on real-world problems
- University, Master or Ph.D. degree in an analytical field of study (e.g. Computer Science, Engineering, Mathematics, Statistics, or related quantitative field).
- Experience working with technical and non-technical project stakeholders to scope, formulate, deploy, and maintain data science systems
- Strong Python experience
- Experienced in using databases
- Expertise in data analysis and machine learning using python, especially using modules such as stats models, scikit-learn, pandas, sqlalchemy, etc.
- Experience creating and using advanced machine learning algorithms and statistics: Classification and Clustering, Forecasting, Predictive modeling, Recommender Engine, Anomaly detection, Optimization, Simulation, Regression, etc.
- Excellent working knowledge of Reinforcement learning (DynaQ/Q+, SARSA, TD, Monte Carlo).
- Excellent knowledge in MS SQL Server DBA.
- Good knowledge with Microsoft Windows Server Administration.
- Excellent knowledge in Python, SQL and C# Programming languages.
- Excellent Knowledge in cloud orchestration.
- Excellent knowledge in Experience with SSIS, Spark, cloud computing services (e.g. AWS), Hadoop.
- Experience with BI tools such as Tableau, Looker, PowerBI, and DOMO for dashboarding or analysis
- Strong communication, collaboration, and problem-solving skills
- Ability to prioritize work and manage multiple work streams concurrently
- Ability to create data architectures.
- Experience in data applications using large scale distributed systems (e.g. Spark, Hadoop, Pig, and Hive).
- Broad knowledge of ML methods, statistical analysis, and problem-solving skills.
- Knowledge of advanced statistical analysis techniques and concepts, and how to apply them to data sets.
- Familiarity with structured and non-structured data.
- A desire to learn new techniques and technologies.
TORONTO, Ontario, Canada
Technology and Operations
Inclusion and Equal Opportunity Employment
At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work. We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities. We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.
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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at rbc.com/careers.