Jampp is a performance marketing platform for mobile advertisers with challenges that span many technologies, from an extremely scalable and highly available platform to big data tools that allow us to manage the big stream of data. We manage hundreds of instances buying impressions in a global market 24/7 with data centers in 3 continents, processing 150 TB daily, 850K QPS and 55+ billion in-app events per month. In order to pick the best ads and show them to the right people at the right time, we rely on real-time machine learning models (with billions of features) that predict in less than 1ms as well as optimization systems which solve complex constrained problems to maximize global company goals in an iterative fashion.
As a Data Science Engineer you will work with other team members to design, prototype and build scalable distributed optimization and forecasting systems that will be used to enhance the machine learning platform we have.
This is an on-site position in Buenos Aires or Córdoba, Argentina, or remote in other cities. However, in light of the COVID19 outbreak, all jamppers are working remotely and we will be conducting all interviews virtually for the foreseeable future. We will continue hiring as usual.
WHAT YOU'LL DO
- Work creatively and analytically in a problem-solving environment
- Identify key problems, propose and execute innovative solutions
- Standardize best practices for analysis, modeling and experimentation; Develop scalable processes to help the team solve pain points and meet goals.
- Help deepen our understanding of the product, our users, and our business through data.
- Work with the product team to identify opportunities for improvement in our current product line, and for enabling upcoming product opportunities
- Work with massive high-dimensional datasets to develop both generic models as well as fine tune models tailored to specific products.
- Apply statistical and econometric models on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict future user or product performance.
- Work with models currently in production, identify areas for improvement, and make them better by using retraining and hyperparameter searches, then deploy without regressing on core model features - including sampling and estimator design, model selection and hyperparameter tuning.
- BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field
- At least 5 years of coding experience. Python stack is a bonus (pandas, numpy, scikit-learn, jupyter notebooks)
- Feel comfortable interacting and coordination with other tech teams to lead execution
- Experience as a tech lead or mentoring other team members
- Proven database experience.
- Experience communicating the results of analyses with product and leadership teams to influence the product strategy and roadmap.
- Be comfortable writing well-structured, production-ready code to support your work and have quality results.
- Smarts, humility, and equal willingness to learn and teach
WHAT WE OFFER
- 📱Learn a ton about the hottest area of growth in Internet advertising - Mobile!
- 💰Competitive salary
- 🤓 Continuous training with a supportive team. We win together.
- 📈 A great level of responsibility from day one and the chance to develop your potential without limitations.
- 💪🏼 An entrepreneurial environment.
- A guaranteed Global Environment! We have jamppers from 🇧🇷🇬🇧🇺🇸🇮🇪🇫🇷🇩🇪🇦🇷🇷🇺... our customers are not the only ones from around the globe 😉
- 😎 Cool swag and team activities. Did we mention an annual off-site?
WHO WE ARE
Jampp is the programmatic platform of choice for the fastest growing on-demand companies worldwide.
In 2013, we noticed the chaos surrounding mobile performance advertising and wanted to change it, somehow. We built a suite of growth products that unlock programmatic advertising for some of the biggest names in mobile (like Uber, Rappi, iFood, & Postmates to name a few).
We’re a team of builders - engineers, data architects, designers, and entrepreneurs - who love what we do.
We serve a global customer base from our offices in San Francisco, Berlin, São Paulo, Singapore, and Buenos Aires.