Halifax, NS, Canada | Technology and Digital Media | Experienced | Full-time
STI Technologies Limited is a healthcare technology company that manages patient support programs. We improve access to medications by leveraging available reimbursement funding and innovative technology to engage patients in their own healthcare.
Through technology and with patients at the heart of our innovations, we proudly support the Canadian healthcare system by delivering intelligent financial reimbursement, patient engagement, and patient management solutions to help support positive health outcomes.
The Data Solutions department at STI Technologies Limited uses advanced analytics to provide actionable insights to our clients, both internal and external. As the guardians of the data, we meet with our clients to help them identify their business questions and then work together as a team or individually to propose, engineer, and deliver solutions.
- Perform a variety of advanced qualitative and quantitative analyses on large datasets, leveraging multiple tools to manipulate, analyze, and visualize the data.
- Consult with internal and external individuals and groups from a variety of backgrounds to identify business needs and architect solutions.
- Successfully breakdown complex concepts and findings to communicate insights in laymen terms.
- Manipulate and transform data to optimize analyses and verify data for accuracy and completeness.
- Provide expertise on mathematical/technical concepts for the broader applied analytics team.
- Work creatively with an eye for innovation, enriching your own deliverables as well as those of your teammates.
- Strategically manage your time and prioritize requests.
- A University Degree in Statistics, Mathematics, Computer Science, Physics, or Engineering
- SQL skills, or other programming experience and the ability to learn new languages quickly and independently.
- A strong work ethic and the ability to think creatively and holistically, going from a ‘business problem’ to a solution with minimal instruction.
- Alteryx, R, SAS, SPSS experience is an asset.
- Knowledge of applied statistics (non-linear regression, contingency tables, GLM, cluster analysis, time series regression, etc.) or machine learning (supervised and unsupervised learning, neural networks, clustering algorithms, etc.) is an asset.
- Data Analytics
- Data Analysis
- Please submit resume and cover letter
- Closing date for applications is Sunday, July 23, 2017.
- Applicants will be updated of their status throughout the selection process