data analyst jobs



About Us
Maharishi Foundation International (MFI) is a US-registered non-profit that supports the development of new technologies and outreach opportunities for the worldwide Transcendental Meditation® (TM®) organisations. Over the past 60 years, more than 10 million people worldwide have learned the TM technique through personal instruction by tens of thousands of certified teachers. 

MFI is a growing, fully remote team of approximately 50 people, located around the globe but mainly in North America and Europe. As an organisation we are committed to leveraging modern technology and progressive management practices to make the TM technique and its related programmes more available to people everywhere. 

We favor a healthy and balanced work environment with opportunities for personal development.

Job Summary
We are seeking a curious and motivated Data Analyst to join our team to be responsible for using data to help the product and engineering teams understand the performance of our current products as well as generating actionable insights to shape our product strategy going forward. You will be the expert in our organisation in turning data into insights – both in scalable, repeatable ways and in novel exploratory ways too. This role is remote and reports to the team lead in Czechia.

About You
You love to work with data as much as you enjoy communicating your findings to an interested audience. You are excited about finding ways to help our product and engineering teams to provide more value to our customers using insights derived from data. You are comfortable working at the interface between business, analytics and engineering. You are a strong team player and know that results come from great people working together around meaningful ideas. You are excited by our mission and want to help us achieve it.

Responsibilities
  • Using data to identify, prioritize and answer questions essential to the product discovery and development process
  • Generating actionable insights to shape our product strategy via exploratory data analyses
  • Enabling data-informed decision making by defining, implementing and monitoring key metrics in dashboards
  • Supporting the planning process by forecasting impact of potential new features
  • Aligning tracking requirements with product and engineering teams
  • Informing the work of the product team by communicating relevant insights effectively


Skills and Qualifications
  • 4-6 years of experience in data analytics role
  • Very strong proficiency in SQL
  • At least 3 years of experience with at least one statistical programming language (R or Python are a plus)
  • Strong analytical thinking and product management knowledge
  • Experience with A/B testing and its statistical foundations
  • Strong knowledge of descriptive statistics, intermediate knowledge of inferential statistics
  • At least 3 years of work experience in a digital product company
  • Excellent communication and prioritization skills
  • Ability to translate business requirements into actionable metrics and analyses
  • Motivated for self-improvement and a healthy lifestyle, and open to / interested in meditation
  • Excellent communication, presentation, and interpersonal skills
  • Fluency in English (written and verbal)
  • Ability to work autonomously and remotely

If you are passionate about this work but do not have all of the skills listed we are still interested in speaking with you and encourage you to apply!

Pay and Benefits
Our pay levels are set according to a formula that combines above-median market rate data for the role (we pay 65th percentile of market rate for this role, based on Payscale data) adjusted for your local cost of living based on Numbeo data.
 
We take the issue of equitable pay very seriously, and we apply our pay formula to all workers who work 80% or more of full time hours with us.

Diversity and Inclusion
We care about diversity, but we know we need to do better. We strive to ensure that all of our team feel included and can bring their whole selves to work but we also know that this work is never ‘done’ or complete, and that we can always improve.