Senior Data Scientist – Machine Learning

  • Job Type: Permanent
  • Location: Europe - Czech Republic - Prague Czech Republic Prague
  • Date Posted: February 13, 2020
  • Salary: 50,000- 70,000
Upload your CV/resume or any other relevant file. Max. file size: 50 MB.
Read about how HFG uses the data that you provide by clicking here: HFG Policies and Statements

FPG looking for a Senior Data Scientist – MACHINE LEARNING

ML Data Scientists to join an amazing team. They deal with terabytes of data from multiple data sources and we are constantly applying ML and NLP and quantitative methods to address a number of marketing objectives.

Are you have to be passionate about solving challenging problems?

Are you have to be excited to learn new things?

Will your solution to have a significant measurable impact?

Responsibilities

  • You will be doing predictive modelling and Optimization: Develop ML models and pipelines for Big Data solutions on the AWS ecosystem by using PySpark, Scikit-learn and R.
    the projects will be monitoring and reporting: Evaluating model performance and help business with Ad-hoc reporting for making proper business decisions.
  • Doing adoption to new technologies/areas: Able to adopt for new programming languages, learn and develop solutions for different subject areas, from NLP to Image.
  • Programing support: Help and provide quick coding of the algorithms and test on the bigdata AWS platform.

Requirements as a Senior Data Scientist – Machine Learning:

  • You must have hands-on experience on AWS and PySpark and PySpark ML with proficiency in R and SQL
    if you have an excellent understanding of ML algorithms: unsupervised and supervised machine learning techniques and methods on large datasets
  • Exceptional attention-to-detail with the ability to meet aggressive deadlines.
  • Team player with good communication skills
  • We move at a fast pace and generally have 3-5 projects going at any one time.

Qualifications

  • BSc or MSc in computer science, or similar computational discipline, e.g. Statistics, Mathematics, Physics (or equivalent experience)