Job Summary: 

• Create new Reports in PowerBI based on the requirement documents
• Consult to get used to Data Lakes based on MS Azure
• General Interface Configuration
• Data Selection/Data crunching
• Understand the Big Data repository
• Provide Data Analysis expertise during project phases
• Perform data visualization and prototyping
• Consult the development team and the Product Owners in all use case studies related to data consumption and data analysis
• Translate HR business problems according to the requirement documents into analytical questions to provide actionable insights and recommendations
• Large data sets from a variety of domains (SAP HR BW, Cornerstone Cloud, Excel)
• Consult HR according to the requirement documents with HR with data-driven decision making through automated dashboards (PowerBI) and statistical analysis

Skills on Resume: 

• PowerBI Reporting (Hard Skills)
• Azure Data Lakes (Hard Skills)
• Interface Configuration (Hard Skills)
• Data Crunching (Hard Skills)
• Big Data Knowledge (Hard Skills)
• Data Visualization (Hard Skills)
• Team Consulting (Soft Skills)
• HR Analytics Translation (Soft Skills)

Job Summary: 

• Develop robust machine learning models.
• Mentor the machine learning team, ideate, and design solutions through teamwork.
• Extract huge volumes of data from multiple internal and external sources.
• Develop data pipelines and infrastructure to scale and automate the analyses that enable rapid product iteration.
• Develop strategies for maintaining QA for the machine learning models.
• Maintain the team's best research and engineering practices.
• Work closely with Data Analysts, Software Engineers, and Project Managers to deliver insights and impactful solutions for the company.
• Devise a data mining process and System architecture.
• Being up to date with the state-of-the-art (deep learning) methods in text and image processing.
• Explore and examine data from a variety of angles to determine hidden weaknesses, trends, and/or opportunities.
• Employ sophisticated analytics programs, machine learning, and statistical methods to prepare data for use in predictive and prescriptive modeling.

Skills on Resume: 

• ML Model Development (Hard Skills)
• Team Mentoring (Soft Skills)
• Data Extraction (Hard Skills)
• Pipeline Development (Hard Skills)
• QA Strategies (Hard Skills)
• Best Practices (Soft Skills)
• Cross-Team Collaboration (Soft Skills)
• Data Mining (Hard Skills)

Job Summary: 

• Take a hands-on role to help meet or exceed ML project requirements (in partnership with other business and data teams)
• Design and build a high-quality, reliable data infrastructure that meets all performance and functional criteria
• Perform exploratory data analysis, data visualisation of various types of data, including but not limited to numerical, text, image, audio, video data, etc
• Build up data transformation pipelines to clean and format data at scale for Machine Learning purposes
• Take an active role to ensure that all problems are resolved thoroughly and validated through appropriate test methods
• Design and develop clean, documented, and easy-to-maintain code.
• Detail and maintain supporting documentation to ensure data governance, risk, and privacy requirements are met, and for ease of accurate project handovers to downstream teams
• Communicate between all relevant teams (internal and external) to ensure effective and timely input and collaboration
• Derive a plan for work to meet project and design goals promptly
• Work independently and as part of a wider team to manage tasks with competing priorities.

Skills on Resume: 

• ML Project Delivery (Hard Skills)
• Data Infrastructure Design (Hard Skills)
• Exploratory Data Analysis (Hard Skills)
• Data Pipeline Building (Hard Skills)
• Problem Resolution (Soft Skills)
• Clean Code Development (Hard Skills)
• Documentation Management (Hard Skills)
• Team Communication (Soft Skills)

Job Summary: 

• Develop features and models to improve the capabilities of systems that use machine learning
• Scale up models, build training datasets, and tune parameters to improve system performance
• Review and implement state-of-the-art machine learning algorithms
• Build software that improves the rate of experimentation
• Keep track of the latest AI research relevant to the business domain
• Design and develop machine learning and deep learning systems
• Design, implement and test technical solutions in the backend
• Implement appropriate ML algorithms
• Prepare technical, operational and user-related documentation in support of applications.

Skills on Resume: 

• Feature Development (Hard Skills)
• Model Scaling (Hard Skills)
• Algorithm Implementation (Hard Skills)
• Experimentation Software (Hard Skills)
• AI Research Tracking (Hard Skills)
• ML System Design (Hard Skills)
• Backend Solutions (Hard Skills)
• Documentation Writing (Hard Skills)

Job Summary: 

• Building and extending production machine learning systems at scale based on open source and enterprise products
• Contributing to open-source projects to extend their functionality
• Architecting solutions for critical industry machine learning systems
• Identifying and documenting best practices for ML Engineering
• Optimising the performance of machine learning systems
• Designing and delivering high-impact solutions with top-tier organisations
• Contributing to global technology conferences

Skills on Resume: 

• ML System Scaling (Hard Skills)
• Open-source Contribution (Hard Skills)
• Solution Architecture (Hard Skills)
• Best Practice Documentation (Hard Skills)
• ML Performance Optimization (Hard Skills)
• Solution Delivery (Soft Skills)
• Conference Contribution (Soft Skills)
• High-impact Design (Soft Skills)

Job Summary: 

• Research and prototype appropriate machine learning algorithms and tools to address real-world client problems
• Work with consultants to design machine learning systems that address business requirements
• Identify, source, and prepare appropriate datasets
• Develop machine learning applications
• Iterate and optimise machine learning systems by designing and running experiments
• Work with ML Ops specialists to design, deploy, and manage the ML lifecycle
• Keep on top of developments in the field
• Identify and explore opportunities for applying ML both internally and on client projects

Skills on Resume: 

• ML Prototyping (Hard Skills)
• System Design (Hard Skills)
• Dataset Preparation (Hard Skills)
• ML Application Development (Hard Skills)
• System Optimization (Hard Skills)
• ML Ops Collaboration (Soft Skills)
• Field Awareness (Hard Skills)
• Opportunity Exploration (Soft Skills)

Job Summary: 

• Planning methodical approaches to tackling difficult ML problems
• Keeping up-to-date with the latest research in 3D ML
• Building feature engineering pipelines and analysing data
• Designing state-of-the-art ML model architectures
• Training and evaluating models and iteratively improving on them
• Contributing to brainstorms
• Sharing subject matter expertise
• Working collaboratively with the ML Lead and the wider team

Skills on Resume: 

• ML Problem Solving (Hard Skills)
• 3D ML Research (Hard Skills)
• Feature Engineering (Hard Skills)
• Model Architecture Design (Hard Skills)
• Model Training (Hard Skills)
• Brainstorm Contribution (Soft Skills)
• Subject Expertise Sharing (Soft Skills)
• Team Collaboration (Soft Skills)

Job Summary: 

• Design and implement new predictive machine learning and artificial intelligence algorithms
• Extract novel insights from healthcare datasets to improve outcomes and economics of care
• Identify and formulate analytical problems underlying major healthcare challenges
• Design experiments and conduct rigorous analytical studies for evaluation and improvement
• Conduct exploratory data analysis and visualization
• Work closely with engineering teams to turn methods into production-ready technologies
• Engage with a growing customer base to define opportunities

Skills on Resume: 

• Algorithm Design (Hard Skills)
• Insight Extraction (Hard Skills)
• Analytical Problem Formulation (Hard Skills)
• Experiment Design (Hard Skills)
• Data Analysis (Hard Skills)
• Engineering Collaboration (Soft Skills)
• Production Deployment (Hard Skills)
• Customer Engagement (Soft Skills)

Job Summary: 

• Be an evangelist for Machine Learning capability, from coding prototypes to generating executive strategy to distributing educational materials. 
• Responsible for prototyping advanced Machine Learning methods.
• Rapidly explore many different methods to weigh pros and cons.
• Identify the best tools for the task and apply those techniques.
• Implement new methods and advance the state of the art.
• Digest papers, conference proceedings, books, and classes for new methods.
• Create plans and schedules, track progress and provide educational material and frameworks to fellow engineers and product managers.
• Work closely with Engineering/Product Managers to develop paths for meaningful research direction.

Skills on Resume: 

• ML Evangelism (Soft Skills)
• ML Prototyping (Hard Skills)
• Method Exploration (Hard Skills)
• Tool Selection (Hard Skills)
• Method Implementation (Hard Skills)
• Research Digesting (Hard Skills)
• Educational Material Creation (Soft Skills)
• Research Collaboration (Soft Skills)

Job Summary: 

• Own the success of assigned projects through careful consideration of requirements and strong execution of the solution build
• Design analytical methods to support novel approaches to data and information processing
• Train, develop, and validate machine learning algorithms on hospital data
• Build end-to-end data pipelines for machine learning models with strong quality control checks and bias assessment
• Rapidly prototype models for exploratory analysis and assess project viability
• Generate and test working hypotheses
• Support the build of the MLOps environment by articulating requirements, assessing the experience from a data science perspective
• Provide technical support for program management and business development activities, including proposal writing and customer development
• Develop and support training and development opportunities for SickKids staff who want more opportunities to use machine learning

Skills on Resume: 

• Project Execution (Soft Skills)
• Analytical Method Design (Hard Skills)
• ML Algorithm Training (Hard Skills)
• Data Pipeline Building (Hard Skills)
• Model Prototyping (Hard Skills)
• Hypothesis Testing (Hard Skills)
• MLOps Support (Hard Skills)
• Technical Support (Soft Skills)