Senior Data Analyst, Remote

• At least 2-3 years of 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 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)
• An attitude to “get stuff done” particularly around being actively involved with data cleaning, 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

Desirable

• Senior Data Analyst, Revenue Analytics is a crucial hire not only for our Revenue Analytics team, but for Remote more broadly
• This individual will help spearhead the advanced analytics capability at Remote, building predictive models within Sales & Marketing, generating insights, and test hypotheses around what drives revenue growth
• In addition, there will be a traditional Reporting & Analytics component to the role (so, it will be a roughly 50% Data Scientist & 50% Data Analyst split in responsibilities in practice)
• As the first Data Scientist, the person has a unique opportunity to bring advanced craft to Remote, develop both new solutions and ways of looking at existing processes, and raise the standards of what is possible using data and machine learning across the entire organization
• Depending on candidate qualifications, expertise and desires, this role can develop into different areas in the future
• 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 6-9 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
• 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 the data science domain technically, creating new knowledge as well as raising the standards for advanced analytics work
• You'll report to: Director of Revenue Analytics
• Direct reports: None
• Team: RevOps - GTM Analytics

• Roughly 4 hours across 4 weeks
• Interview with Recruiter (30-45 mins)
• Interview & Live Technical Assessment with future manager (90 mins)
• Interview with Team Members (no managers present) (45 mins)
• Executive Interview (30 minutes)