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- Tasks: Lead data science projects, from analysis to deployment, transforming healthcare with advanced analytics.
- Company: Join a forward-thinking healthcare client focused on innovative data solutions.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real difference in healthcare by bridging business needs with cutting-edge data science.
- Qualifications: Proven experience in data science, machine learning, and stakeholder management is essential.
- Other info: Dynamic role with opportunities to mentor and lead in a collaborative environment.
The predicted salary is between 36000 - 60000 £ per year.
Our healthcare client is seeking a Lead Data Scientist to bridge the gap between business needs and advanced analytical solutions. This is a full-time permanent position with a hybrid work model, requiring on-site presence 1-2 times a month in Markham, ON. Fully remote options are available for candidates located outside of the GTA.
The successful candidate will own the end-to-end analytics lifecycle, from understanding complex healthcare workflows to deploying data science and machine learning models in production. This position requires proficiency in stakeholder management and technical implementation, leading both the discovery of opportunities and the delivery of solutions.
The scope of work includes:
- Stakeholder management
- Requirements gathering
- Leading workshops
- End-to-end Data Science and Machine Learning (ML) accountability
- Data discovery and exploratory data analysis (EDA)
- Creation of compelling data visualizations/reporting
- Deployment and testing
Must Haves:
- Data Science & Machine Learning
- Python programming (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch)
- Experience leading discovery shops is mandatory
- Strong statistical knowledge and experimental design
- Experience with Azure ML or similar cloud ML platforms is a strong asset
- Model lifecycle management experience
- Analytics & BI Understanding
- General knowledge of modern BI/analytics platforms
- Experience with SQL and data manipulation
- Proven track record and extensive experience leading requirements gathering for complex analytical projects
- Proven track record of translating business needs to technical solutions
- Experience with process mapping and workflow analysis
Key Responsibilities:
- Data Science & Machine Learning Leadership
- Technical Development
- Guide and mentor exploratory data analysis (EDA) and feature engineering efforts
- Design, develop/code, and validate machine learning models
- Conduct advanced statistical analysis to derive model selection and training
- Model Development: Lead end-to-end ML project development including EDA, feature engineering, model selection, training, and validation
- Azure ML Implementation: Oversee design and implementation of ML pipelines using Azure ML, including model deployment, monitoring, and retraining
- Statistical Analysis: Conduct advanced statistical analysis, hypothesis testing, and model validation using appropriate methodologies
- Technical Team Leadership
- Project Management: Lead cross-functional ML projects from conception through deployment and monitoring
- Peer Review: Conduct technical reviews of ML models, code quality, and deployment strategies
- Lead and mentor data scientists and analysts
- Establish technical standards for ML development
- Oversee and collaborate with data engineers on ML pipeline design
- Identify and help prioritize machine learning use cases across the organization
- Champion adoption of predictive analytics in operations
- Manage and evolve the GoTool AI/MLOps platform
- Ensure platform reliability and performance
- Drive platform enhancements based on user needs
- Manage quarterly model refreshes and updates
- Coordinate with stakeholders on platform roadmap
Business Analysis & Requirements Leadership
- Stakeholder Engagement & Discovery
- Lead comprehensive requirements gathering using diverse methodologies
- Facilitate analytical discovery sessions with clinical and operational leaders
- Map complex healthcare workflows to identify analytics opportunities
- Build deep understanding of departmental value chains and pain points
- Solution Design & Consulting
- Translate business problems into analytical solution architectures
- Create business cases for predictive analytics initiatives
- Lead end-to-end analytical solutions spanning reporting to ML
- Present complex analytical concepts in business-friendly language
- Develop roadmaps aligning analytics capabilities with business strategy
- Project Leadership
- Lead cross-functional analytics projects from conception to value realization
- Manage stakeholder expectations throughout project lifecycle
- Ensure analytical solutions integrate seamlessly with business processes
- Measure and communicate business impact of deployed solutions
Lead Data Scientist to bridge the gap between business needs and advanced analytical solutions in London employer: S.i. Systems
Contact Detail:
S.i. Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist to bridge the gap between business needs and advanced analytical solutions in London
✨Tip Number 1
Network like a pro! Reach out to connections in the healthcare and data science fields. Attend meetups, webinars, or even local events. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving machine learning and analytics. Use platforms like GitHub to share your code and visualisations. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and stakeholder management skills. Be ready to discuss how you've translated business needs into analytical solutions in the past. Practice common interview questions related to data science and ML.
✨Tip Number 4
Don't forget to apply through our website! We often have exclusive listings that you won't find elsewhere. Plus, it shows you're genuinely interested in joining our team. Keep an eye on new openings and get your application in early!
We think you need these skills to ace Lead Data Scientist to bridge the gap between business needs and advanced analytical solutions in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience in data science and machine learning, especially any leadership roles you've had. We want to see how you can bridge the gap between business needs and analytical solutions!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of how you've led projects or managed stakeholders in the past. Remember, we love a good story that showcases your skills!
Showcase Your Technical Skills: Don’t forget to highlight your technical prowess! Mention your experience with Python, Azure ML, and any other relevant tools. We’re looking for someone who can own the end-to-end analytics lifecycle, so make sure we see that in your application.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at S.i. Systems
✨Know Your Data Science Stuff
Make sure you brush up on your data science and machine learning skills, especially in Python and libraries like NumPy and Pandas. Be ready to discuss your experience with model lifecycle management and how you've applied statistical analysis in past projects.
✨Show Off Your Stakeholder Skills
Prepare examples of how you've successfully engaged with stakeholders in previous roles. Highlight your experience leading discovery workshops and translating complex business needs into actionable analytical solutions. This will show that you can bridge the gap between technical and non-technical teams.
✨Demonstrate Your Project Management Prowess
Be ready to talk about your experience managing cross-functional projects from start to finish. Discuss how you've led teams through the analytics lifecycle, ensuring that solutions are not only technically sound but also aligned with business objectives.
✨Visualise Your Success
Bring along some compelling data visualisations or reports you've created in the past. This will help you demonstrate your ability to communicate complex analytical concepts in a way that's easy for stakeholders to understand, which is crucial for this role.
