Machine Learning Engineer

Barcelona, Barcelona, Spain
Full Time
Experienced

Smadex (www.smadex.com) is a leading advertising technology company founded in Barcelona in 2011 and sold to American-based and stock-listed Entravision in 2018 (NYSE::EVC). We are currently considered one of the top mobile ad-tech companies in the world, competing with American-based Liftoff and Korean-based Moloco, both pre-IPO stage and averaging about $500M in yearly revenues.

We compete in a highly advanced technology-driven industry where Data Science and cutting-edge cloud-based big data architectures make all the difference in the company’s growth. 

We are looking for ambitious engineers whose ultimate motivation is to learn the most advanced technologies used in the ad-tech industry by the likes of Google and Facebook and to help us become the biggest mobile programmatic advertising platform in the world.

Our mission is to continue to improve our ad-tech platform to help our clients achieve their programmatic advertising campaign goals, and we want to give our employees a job they’ll love, where they will be challenged to improve results through real-life engineering and data analysis and where everyone’s implication has an impact. 

Are you ready to be part of the new unicorn? Keep reading!

What will you do:

  • You will be deeply involved in all the major architectural and development decisions we make on our algorithms
  • You will be responsible for developing new features, measuring the performance and improving our pipelines. Our ML Engineer role combines the classic "ML Scientist" and "Data Engineer" role at other companies
  • You will also play an analytical role researching, designing, implementing, and deploying full-stack scalable data analytics and machine learning solutions to challenge business issues, as well as working closely with our Tech and Ops team
  • You will work on unique modeling challenges not covered in the scientific literature, like extreme positive sample sparsity and labelling delay.
  • Analyse data from different sources and provide actionable insights to business and engineering stakeholders

What you need to have:

  • 5+ years of relevant experience in data science positions
  • Very strong coding ability: Python, Scala, Java
  • Proficiency in building high-performance algorithms in production
  • Proficiency in solving problems
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical significance tests)
  • Experience in data mining and predictive modelling inclusive of logistic regression, clustering and time series analysis models 
  • Knowledge of Bitbucket/Git version tools
  • Experience working with SQL and data warehousing
  • Possesses excellent communication skills both verbal and written
  • Able to mentor other team members
  • Fluency in English

Extra points for :-)

  • Master’s degree in Statistics, Applied mathematics, Computer Science
  • Experience with reporting and data visualization tools such as Jupyter Notebook, Zeppelin, Tableau, Periscope, PowerBI or others
  • Experience in digital marketing platforms and user acquisition
  • Experience with and Apache Spark and Nodejs programming language
  • Familiarity with AWS services such as EMR, EC2, Athena, S3, Redshift
  • Used to Linux environments

Reward package:

  • Integrate a highly motivated and young team
  • Great compensation package
  • Top location at the heart of Barcelona in a penthouse office with rooftop terrace, Barbeque and fully stocked fridge
  • Good work-life balance: work from home, flexible hours
  • Learning and training opportunities
  • Meal vouchers - Tickets Restaurant monthly allowance 
  • Monthly gym allowance to use in up to the 30 DIR gyms around the city
  • Monthly TGIF events
  • Regular team-building events
  • Fun and friendly work environment with talented marketers and engineers from over 21 countries
  • Exposure to leading global app publishers (Zynga, King, Rovio, EA, etc.) and media partners in the digital advertising industry
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