Family Podiatry Centre – Certified Data Analytics (R) Specialist

The Family Podiatry Centre offers the best treatment for TOES, FEET, ANKLES, KNEES, AND LOWER BACK PAIN, by using a wide range of modalities including custom made orthotics using CAD/CAM technology, therapies such as shock wave therapy (ESWT), taping, exercises and PHYSIOTHERAPY

You will need to provide data analysis and insights to product owners and business stakeholders to support business decisions. Other responsibilities are as follow:

• Produce and automate reports for the global finance team to perform accuracy checking.

• Maintain and/or develop web-crawlers to automate data checking between client’s website and company database.

• Collaborate with other Product Owners to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, product analysis and expected deliverables.

• Fulfill ad-hoc data request from different product owners.

Responsibilities

• Be the first member of a critical and growing team that helps the business take better decisions and build the data culture in the company.

• This role sits within the product team, so you work very closely with business, engineering and operations to help teams with data analysis, insights and visualizations

• Be obsessed with data accuracy and collaborate extensively with data engineers to create a fast and reliable data pipelines

• Understand data to arrive at hypotheses to test, and then drive the process of running, measuring and optimizing experiments with the product team.

• Creating dashboards that are used for monitoring user behaviour, growth, reliability and other critical KPIs of the org.

• Identifying, onboarding and training on the right stack of tools needed for the data requirements

• Analyze and document business processes, and identify areas for improvement and optimisation

- hands-on experience on data manipulation tools like SQL, R, SAS, Python, Excel etc.

• Hands-on experience on BI Platforms like Power BI, Tableau etc.

• Excellent knowledge of statistical measurement frameworks (measures of central tendency, dispersion, distribution, significance testing etc.)

• Knowledge of commRegression, Classification etc.