Senior Data Scientist Job at BMO। New Vacancy। Apply

Job Title : Senior Data Scientist

Salary : $81,600–$151,200 a year

Location : 100 King Street West, Toronto, ON

Company : BMO Financial Group

Qualification : Doctoral degree

Experience : 2-8+ years

ABOUT BMO FINANCIAL GROUP

BMO Financial Group, centered in Toronto, is one among Canada’s biggest and oldest monetary establishments. Established in 1817, the financial institution operates because the Bank of Montreal, imparting a broad range of monetary offerings inclusive of personal and commercial banking, wealth management, and investment services.

With a sturdy presence in North America and choose worldwide markets, BMO specializes in turning in complete answers tailored to the wishes of man or woman and corporate clients. The agency is understood for its dedication to innovation, sustainability, and community involvement. Through its various economic services, BMO targets to assist clients reap their monetary dreams whilst contributing definitely to the communities it serves.

Job Overview

A Senior Data Scientist leverages advanced statistical analysis, gadget studying, and records modeling techniques to pressure strategic decisions. They lead information-pushed tasks, layout and implement complex algorithms, and interpret massive datasets to provide actionable insights. Their position includes taking part with move-practical teams, mentoring junior records scientists, and making sure the integrity and accuracy of statistics processes. They often paintings on optimizing enterprise methods, identifying developments, and growing predictive models to remedy complicated problems and support commercial enterprise objectives. Strong analytical competencies, know-how in facts tools, and a deep expertise of statistical methodologies are crucial.

Responsibilities Of a Senior Data Scientist:

• Data Analysis and Modeling: Develop and implement complex statistical models and machine learning algorithms to analyze big datasets. Interpret and communicate findings to offer actionable insights that help enterprise choices.
• Project Leadership: Lead records technological know-how tasks from inception to of entirety, along with trouble scoping, facts collection, version improvement, and deployment. Oversee mission timelines and ensure deliverables meet pleasant standards.
• Cross-Functional Collaboration: Work intently with stakeholders, which include product managers, engineers, and bosses, to understand commercial enterprise needs and translate them into technical requirements. Ensure that facts solutions align with strategic goals.
• Mentorship: Provide steerage and mentorship to junior facts scientists and analysts. Share information, evaluate work, and make a contribution to their professional development.
• Data Management: Oversee the collection, cleansing, and validation of statistics. Ensure facts first-rate and integrity while adhering to statistics privacy and protection protocols.
• Algorithm Development: Design and construct scalable algorithms and information pipelines. Optimize current algorithms for overall performance and efficiency.(Senior Data Scientist) 
• Reporting and Visualization: Create and gift specific reports, dashboards, and visualizations that efficiently speak complex statistics insights to non-technical stakeholders.
• Innovation and Research: Stay updated on industry trends, rising technology, and advancements in statistics technological know-how. Apply new strategies and tools to beautify records analysis skills.
• Problem-Solving: Address complex enterprise problems using quantitative and qualitative strategies. Develop progressive answers based on data-pushed insights.

Qualifications Of a Senior Data Scientist:

1. Educational Background: A Master’s diploma or Ph.D. In Data Science, Statistics, Computer Science, Mathematics, or a associated discipline is frequently required.
2. Experience: Proven revel in as a statistics scientist with a robust portfolio of a success initiatives. Typically, 5-7 years of applicable revel in, together with full-size experience with advanced device gaining knowledge of and statistical strategies.
3. Technical Skills: Proficiency in programming languages which include Python, R, or SQL. Experience with statistics manipulation, statistical analysis, and gadget getting to know libraries (e.G., scikit-analyze, TensorFlow, PyTorch).
4. Analytical Abilities: Strong problem-fixing talents with the ability to research and interpret complex data. Expertise in statistical evaluation and data modeling.
5. Communication Skills: Excellent verbal and written communication abilities.Ability to give technical records to non-technical audiences really and concisely.(Senior Data Scientist) 
6. Tool Proficiency: Experience with data visualization tools (e.G., Tableau, Power BI) and big statistics technologies (e.G., Hadoop, Spark) is tremendous.
7. Project Management: Strong organizational abilities with enjoy managing a couple of initiatives and assembly time limits.
8. Collaboration: Ability to paintings correctly in a team environment and collaborate with pass-practical groups to achieve commercial enterprise goals.

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