Position: Data Scientist/Machine Learning Engineer
Company: Surprise
Experience required: 3y
English level: intermediate

**Your impact:**
As a Machine Learning Engineer at Surprise.com, you will have the ability to shape our application, as well as to help us bring better appreciation and engagement to employees of companies around the world. You’ll work in conjunction with our front-end developers, designers, Product organization, and the rest of the company, in order to help us build delightful and performant software. You’ll have input into the technical roadmap, providing guidance on how to build scalable technical solutions. And you’ll help us figure out how to make the best use of our data, to give new insights to businesses.

**Your typical day:**
Research, design and implement machine learning algorithms
Automate manual processes and optimize data pipelines, interpret it in an interactive way
Consulting performance from a technological and scientific perspective
Delivery rapid prototypes and proof of concepts that demonstrate real value
Communicating results, technical constraints, and decisions to the business and non-specialists
Creating and delivering progress reports, slide decks, proposals, and documentation

**Requirements**
Extensive knowledge and practical experience in Machine Learning, Recommender Systems, and Algorithms
Experience in software developmen 4+ years
Experience in Data Science 2+ years
Understanding of Machine Learning techniques like Linear Regression, Decision Trees, Collaborative Filtering, Anomaly Detection, etc.
Practical experience with high-level programming language Python and framework
Proficiency in using database query languages such as SQL and understanding of the ETL process
Knowing of Linear Algebra, Probability and Statistics and Numerical methods
Understanding of software development process, Agile approach, and CI/CD
Degree in computer science or related field
Upper-Intermediate English level or higher

**Nice to have:**
Building large-scale recommender engines (collaborative filtering, KNN, associative rule learning, custom similarity metrics, etc.)
Predictive analytics (time-series analysis and forecasting, survival and duration analysis, etc.)
Applying graph analysis techniques for structural pattern recognition Applied statistics skills, such as distributions, hypothesis testing, regression analysis, etc.
Building microservices and containerized applications (Docker, k8s)
Big Data frameworks — Hadoop, Spark Experience with Natural Language Processing NoSQL databases, such as MongoDB, Cassandra, HBase
Experience with mining of structured, semi-structured, and unstructured data
RESTfull API creation in Python (Flask, Falcon or similar)
Experience with data visualization tools, such as Ggplot2, Plotly, Matplotlib

**Benefits**
Friendly and highly professional team
Flexible working hours
20 working days of paid vacation
English lessons and English speaking club with a native speaker
Modern comfortable office with all amenities
15 days of paid sick leave
Snacks and fruit in the office kitchen:)