переезд (New York, USA) или полная удаленка — на выбор.
1 - 5 человек
PulsePoint, a global programmatic advertising platform with specialized healthcare expertise, fuses the science of programmatic targeting, distribution and optimization with the art of brand engagement. The PulsePoint platform is powered by terabytes of impression-level data, allowing brands to efficiently engage the right audiences at scale while helping publishers increase yield through actionable insights. Now they are looking for a Machine Learning Engineer.
The goals of the PulsePoint Data Science team
- Optimize and validate targeting mechanisms for specific health conditions.
- Improve and optimize our proprietary contextualization and recommendation engines that handle millions of transactions per second, trillions each month.
- Improve and optimize our buying platform to ensure cost efficiency and to deliver ad campaigns within budget, target and time constraints.
- Collaborate with internal Health experts to design and support rapid assessment, analysis, and prototyping of ideas for achievable commercialization.
Python, Numpy, Scipy, Pandas, Sklearn, Hadoop, Hive, Spark.
Head of Data and Infrastructure.
Why we are recommending
- The PulsePoint platform is powered by terabytes of impression-level data.
- Ability to work with modern technologies.
- Improve existing or develop new traffic segmentation algorithms and estimations of bid landscapes within each segment.
- Optimize real-time bidding strategies to efficiently spend ad budgets delivering campaign targets given various constraints.
- Support and enhance the existing work on health user profiling, prediction, and targeting tools.
- Improve page contextualizer technology: work with healthcare topics detection algorithms, keywords/phrases extraction, general and aspect-based sentiment analysis.
- Contribute on projects relating to patient/physician identity for cross-device tracking, profiling and targeting.
- Support existing codebase for data integration and production support for our core models.
- 3+ years of full-time experience working as a Statistician/ Machine Learning
Engineer/ Data Scientist.
- Advanced knowledge of Big Data technologies such as Hadoop, Hive/Impala and
- Advanced knowledge of Python using the numpy/scipy/pandas/sklearn stack.
- Advanced knowledge of classical ML models (logistic regression, decision trees,
boosting, bagging, SVM, Bayesian methods, etc) and at least basic knowledge in
different Neural Network models (CNN, RNN, auto-encoders, transformers).
- Being confident user of Unix-like systems, Dockers, git, bash.
- MS/PhD in Applied Mathematics, Statistics, Machine Learning, Computer Science,
Physics; or BS with several years of applied machine learning experience.
- Remote work, full time. Relocation and visa support after first 6 months of remote work (London or NY).
- US holiday schedule.
- 4 weeks (20 work days) of paid vacation.
- Flexible schedule except for a daily team call at 20/21 Moscow time.
- (rus / eng) 20-30 min call with a recruiter, talk about experience and check english.
- (eng) 60 min screening.
- (eng) 180 min interview with sections.
- (eng) Sometimes the CEO or CTO talks before the offer.