Senior Data Analyst

Summary

Join Remote's Revenue Analytics team as a Senior Data Analyst and contribute to the company's advanced analytics capabilities. You will build predictive models, generate insights, and create reports for Sales & Marketing. This role involves a blend of data science and data analysis, offering opportunities for growth and development within a modern tech stack. The position is fully remote, with a competitive salary and benefits package. Remote prioritizes a diverse and inclusive workplace and encourages applications from all backgrounds. The ideal candidate possesses strong analytical skills, proficiency in SQL and Python, and excellent communication abilities.

Requirements

• Experience in data science / advanced analytics / statistical modelling experience, ideally within Sales/Marketing/Finance or other commercial parts of the organization
• Working knowledge of workhorse machine learning algorithms (particularly supervised learning using Python), and their typical use cases in a commercial organization
• Insatiable curiosity to proactively pose deeper questions, not be satisfied with superficial answers, and dig into vast granular data to uncover conclusive answers analytically
• Strong proficiency in SQL (in Snowflake) to manipulate data easily
• Demonstrated ability to craft precise analytical questions from ambiguous business problems, and roll up the sleeves to address them
• Understanding of causal inference methods to be able to utilize quasi-experimental or other econometric techniques to determine causality among different initiatives (essentially, finding out “what works,” and what does not, especially around Sales & Marketing questions)
• An attitude to “get stuff done” particularly around being actively involved with data cleaning and quality, building reports or answering important business questions (being a full-stack data professional)
• Top-Tier communication skills in English, to distill complex mathematical models, concepts and findings into simple, intuitive words and charts for senior commercial leaders

Responsibilities

• Initially focusing on developing and maintaining KPIs and dashboards with the rest of the team, to monitor metrics and uncover insights as the primary responsibility for the first ~3-6 months (also to understand the business effectively)
• Liaising productively with Data Analysts, Analytics Engineers and the business teams/owners to ensure that data products, analysis & statistical models built are not only technically sound but highly effective and widely useful
• Building predictive models around different business areas and problems within Revenue Analytics : Lead Scoring, Marketing Attribution, Customer Churn Prediction, Optimizing Sales Processes, Building Books of Business
• Maintaining the data pipelines and statistical models, and also continuously calibrate existing models to account for changing business conditions and/or customer behaviour
• Using causal inference and quasi-experimental techniques to dig into historical & current data to statistically identify which initiatives worked and what was the lift they produced
• Owning important business questions analytically and technically, creating new knowledge as well as raising the standards for advanced analytics work

Preferred Qualifications

• Startup/Scaleup Experience
• AWS Knowledge
• Comfort with distributed & remote teams
• EMEA Location
• SalesForce Data Experience
• Hands-On familiarity with a BI Tool such as Sigma/Looker
• Dbt
• Advanced university degree in Statistics/Mathematics/Physics or other quantitative field
• Go-To-Market (GTM)/Sales Analytics Experience a huge plus
• Some experience of deploying ML models into production ideally highly meriting
• It's not required to have experience working remotely, but considered a plus

Benefits

• Work from anywhere
• Flexible paid time off
• Flexible working hours (we are async )
• 16 weeks paid parental leave
• Mental health support services
• Stock options
• Learning budget
• Home office budget & IT equipment
• Budget for local in-person social events or co-working spaces