Data Analyst - Billing
Barcelona, Catalonia, Spain
Mad Collective
At Mad, we embrace the mad scientist persona! How? We question assumptions. We strive to raise the bar. We guess, test, learn and improve!
Our projects are digital, in industries like VR and marketing services. Our portfolio continues to grow as we seek out exceptional products and ideas to develop and invest in.
We are proud of our diversity (over 32 nationalities) and believe it is one of the most important contributors to our success.
Join the collective and go mad with us!
What will you do?
We are looking for a Data Analyst to join our Billing - Analytics department. This position plays a crucial role in supporting the Billing Team with projects, daily tracking, and analysis. The goal is to explore and understand performance optimization and issue tracking. Through an analytical and business-oriented approach to data, the Data Analyst will enhance billing optimization and help unlock new revenue opportunities.
Responsibilities:
- Help to define and monitor Billing KPIs on a daily basis such as conversion rates, re-bill success, declines and chargebacks.
- Understand business needs and produce insightful, actionable insights.
- Conceptualize, develop, and maintain dashboards and visualizations that inform both tactical and strategic decision making.
- Collaborate with cross-functional teams (Product, Data Engineers, Data Scientists) to plan, facilitate, and develop Billing Analytics projects.
- Enable self-service data exploration, making data standardized and easily accessible.
- Collaborate with stakeholders to collect feedback, educate on new data solutions and promote data culture within the company.
Requirements
The ideal candidate will have at least 2-3 years of relevant industry experience, including 1-2 year with billing/finance knowledge, possess good communication skills, is proactive, independent and result oriented. We are looking for someone who is passionate about challenging billing and payments data problems, enjoys finding interesting insights and suggesting improvements, and applying conclusions to drive clear and practical business improvements.
Must have:
- Experience in a similar role and/or a degree in a quantitative discipline such as Engineering, Computer Science, Mathematics, Economics or related field.
- Proficiency in writing and optimizing SQL queries, specifically with MySQL and Redshift.
- Working knowledge with visualization tools (BigQuery, Tableau, Looker, Qlikview, etc)
- Experience working with R or Python to perform business analysis.
- Excellent problem solving, analytical and critical thinking.
- Good presentation skills in communicating to both experts and general audiences.
- Quality driven, attention to detail and pragmatic.
- Proactive and positive attitude, self-organized and an excellent team player.
- Communicative and empathic with stakeholders.
- Fluent spoken and written English.
Nice to have
- Interest in Data Science and Machine Learning models.
- Experience or exposure to cloud platforms such as AWS or Google Cloud
- Familiarity with version control systems, particularly GitHub
- AB test design and analysis
Benefits
- Private health and dental insurance plan for employees
- Subsidized gym memberships and fitness classes
- Monthly internet allowance.
- Working from home setup allowance
- Sponsored training and development
- Top notch Apple equipment
- Remote policy and flexible working hours
- Flexible Bank Holidays: design your own working calendar with a lengthy consecutive vacation day policy
- Day off for your birthday
- Beautiful office in Barcelona with a terrace and food allowance.
*Please note: All applications must be submitted in English
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS BigQuery Computer Science Economics Engineering Finance GCP GitHub Google Cloud KPIs Looker Machine Learning Mathematics ML models MySQL Python QlikView R Redshift SQL Tableau VR
Perks/benefits: Career development Flex hours Flex vacation Gear Health care Home office stipend
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