Data Scientist

Data Scientist

Client: Not for Profit

Role: Data Scientist

Job Type: Permanent

Location: Preferably Hybrid in Markham, open for Remote EST hrs

Your New Company

Our client, a very well-known banking client looking to hire Data Scientist.

Your New Role:

As part of a multi-faceted collaborative team, the Data Scientist will play a key role in the creation of a next-generation data solutions based on analytics (descriptive, diagnostic, predictive, prescriptive) using statistical modeling, Machine Learning. These solutions will be used by users to support strategic and/or day-to-day decisions. The incumbent will have hands-on involvement in all stages of the project lifecycle focusing on delivering data- driven operational improvements.

This is an operational, hands-on role that is strictly focused on analytical machine learning, MLOps, and practical, operational data science (rather than research).

The Data Scientist works closely with stakeholders across all of as their trusted advisor in making strategic decisions to improve quality, performance, and user experience aspects of our home and community care business. Please note: The incumbent is expected to lead a project end-to-end: gather requirements, lead data discovery, co-design with end-users, gather data, develop/code, train peers, and assist with QA efforts.

Responsibilities:

Become a trusted analytics advisor

• Participate in complex requirements gathering and analysis activities. Understand and document requirements, business needs, processes, and data gaps
• Develop meaningful understanding of data and challenges, as well as broad challenges within home and community sector in healthcare
• Ensure alignment of data solutions with strategic goals and objectives
• Be the point of contact for Data Science based data solutions
• Create innovative data solutions
• Conduct advanced, in-depth exploratory data analysis (EDA)
• Communicate and refine EDA based on stakeholder input, business processes and in consideration of data quality challenges
• Propose ML baseline models based on best practices and sound literature review
• Develop, configure and tune Machine Learning models using Python (via Jupyter, with Pandas or other appropriate libraries as deemed appropriate)
• ADS creation scripts (Python, Pandas, GeoPandas)
• Develop data models and tools to predict, categorize, quantify, and forecast key performance indicators to support strategic decision making and operational improvements (Python)
• Build machine learning models, optimize and deploy new models into production
• Establish scalable, efficient, automated processes for data analysis, machine- learning model development, model validation and serving.
• Perform descriptive and inferential statistical analysis in Python and/or Excel.
• Leverage AI and Machine Learning (using Python) for data discovery, analytics, reporting and strategic business decision support
• Maintain and expand existing Data Science/Machine Learning products and artifacts to ensure continuous growth and improvement
• Propose and Adopt ML/Data Science Technology
• Objectively evaluate different technologies: Azure ML, Databricks and in-house Python-based approach
• Share findings of the evaluation and obtain buy-in from stakeholders
• Find ways to streamline ML processes and its promotion to our production environments
• Share insights
• Develops and presents material to various stakeholders and levels in the
• organization, using excellent written and verbal communications skills, with ability to express complex concepts effectively
• Provide meaningful interpretation of analysis and results
• Train team members on use of vendor-created platforms, Dash, Python, and data science concepts
• Train team members on data pipelines, feature engineering concepts and integration
• Introduce data science capabilities, expertise, and tools to support organizational initiatives and data-driven decision making
• Learn and leverage SE reporting / visualization tools (such as MicroStrategy, Dash) to accommodate and present work
• QA
• Support validation of existing models (QA testing against business requirements)
• Validation/testing of developed artifacts (as well as development of user acceptance testing in collaboration with stakeholders)

What You’ll Need:

• Degree in Science, Mathematics, Computer Science, Information Systems, Health Information Systems, Statistics, or related discipline with a special focus on
• Machine Learning/AI (PhD degree is preferred)
• Project Leadership experience is a must – particularly in large data teams
• Previous project or work experience utilizing AI/ML is a must
• Expert-level Python programming
• Moderate understanding of SQL
• Expert-level understanding of data analytics and data science principles particularly in areas of Machine Learning
• Solid foundations in statistics - experience with statistical data analysis
• Expert-level understanding of ARIMA, clustering methods, MLOps concepts
• Proficiency in developing analytical reports and dashboards to support data-driven decision making
• Excellent verbal, written, and presentation skills
• Self-motivated, ability to take direction, and work independently

Preferred Qualifications:

• Experience in healthcare is considered a strong asset
• Supply chain data analysis, optimization, and forecasting
• Familiar with data lifecycle

What You’ll get in Return

The client is offering a permanent opportunity with competitive benefits

Interested?

If you’re available and interested in this role, please reply to [email protected] as soon as you can attaching your updated resume and hourly rate requirement.