Job Description
How You’ll Make an Impact
As an Analytics Engineer you will be Spearheading Yieldify’s/Epsilon's reporting practices by leading on projects such as developing unique attribution models, applying new statistical interpretations methods, and identifying key drivers of our technology’s success. Being part of the Engineering team, your remit will be global and include customer-facing aspects.
Work together win together:Reporting to our Engineering Manager as part of the Insights squad and collaborating with commercial teams globally in our core markets. This is a hybrid role, with an expectation of 2 days per week in our office in West London.
Innovate with purpose:As an Analytics Engineer you will be at the core of Yieldify’s value delivery, driving insights and training other teams to directly impact how we do things at Yieldify. Being part of the Insights Squad, you will hold high impact in a global role. Working across global teams in our core markets in: EMEA, NA & APACLeading innovative models and data innovation for Yieldify & Epsilon
What You’ll Achieve
Impact:Working in a big data business you’ll have a seat at the table; you’ll partner with internal engineering teams and internal client executives while driving key Yieldify & Epsilon initiatives Leading the reporting vision of the Yieldify business into the wider Epsilon eco-system
Career Growth: If successful, the Analytics Engineer will develop deep analytical skills and learn how to communicate solutions with technical and non-technical colleagues. Our goal is dominate the Mid-Market personalization space and you will be in at the heart of the analytics functions growth.
Who You Are
What you’ll bring with you:
An analytical mind who loves to dive deep into the data, identify patterns and generate insights for the benefit of our customers. Background in applied mathematics and comfort in working with real world datasets. Excellent SQL knowledge with practical application. Experience in big data, multivariate testing, and developing business intelligence. Experience in leading projects such as developing unique attribution models, applying new statistical interpretations methods, and identifying key drivers of our technology’s success. Able to identify improvements to our methodology and processes and help lead their implementation across the company. Able to maintain a high-performance, reusable, and scalable data transformation pipeline for our data warehouse to ensure our clients receive core reporting and business intelligence quickly and efficiently. Experience in working with Data Scientists to design predictive analytics, machine learning models, and automation infrastructure usings thousands of unique data points. Able to discover, transform, test, deploy and document data sources. Knowhow around cleansing current data structures to optimize internal processes and enable more efficient and effective reporting practices
Why you might stand out from other talent:
Experience applying software engineering best practices to analytics. Experience setting-up and maintaining Tableau or Looker reporting or similar. Experience managing data transformation pipelines through DBT and a warehouse like Databricks or similar. A quantitative degree such as Maths, Engineering, Economics or Physics, or equivalent work experience would be preferred
