Position: Big Data/Machine Learning/Algorithm engineer
Category: Data Science
English level: fluent
Years of experience: 11

* Data platform for large financial company
* Small TF-IDF based search engine, vector space model to represent texts, TF-IDF as relevance measure, cosine similarity to find significant words per text/author and to locate texts similar to a given one
* Content-based recommendation engine (TF-IDF, cosine similarity).  PredictionIO, Spark, Java
* Distributed RSS indexer (Java, beanstalkd)
* Search engine for people's profiles in social networks - Elasticsearch, Java, Amazon SQS, Azure, HBase
* Facebook app allowing to index FB friend profiles in Elasticsearch and search them, Scala
* Heuristic algo finding prime constellations, Scala
* A search engine for products for a e-commerce aggregator, some NLP to "understand what client searches for" and to build appropriate request, DFA-based substring search algorithm (Python, NLTK, Elasticsearch, esm-re, Flask, Redis, gunicorn) 
* Trained specific Named Entity Recognition model (Python, NLTK, pycrfsuite) 
* Training neural network with genetic algorithm (Python, Numpy, Scipy, Hadoop Streaming, Amazon EMR, EC2) 
* Clustering large database of products for e-commerce aggregator by similarity to find duplicate products/very similar products 
* Implementing K-Prototype clustering (extention of K-Means) using Artificial Bee Colony evolutionary optimization metaheuristic
* A number of genetic algorithm applications to various problems: neural network training using genetic algorithm, Vehicle Routing Problem (Python, Numpy, matplotlib, Jupiter notebook), hyperopt), knapsack problem (Python, Numpy, Cupy, matplotlib, pandas, Jupiter notebook, hyperparameter optimization with hyperopt, lot of visualizations in process) 
* Visualization of higher dimensional space using Cohonnen network (Python, Numpy, matplotlib)
* Knapsack-like optimization problem (finding optimal distribution of limited funds to get optimal discount). Genetic algorithm for an approx. solution in a limited time, bruteforce algo for the small problems. Artificial Bee Colony algo. Hyperparameter optimization
Linux, Hadoop, Java, HBase, Algorithms, NoSQL, BigData, Pig, CouchDB, Cassandra, AWS, MapReduce, Nutch, ElasticSearch, Scala, machine learning, discrete optimization, evolutionary algorithms, functional programming
Only remote. Interested in projects related to Big Data/Data Science/Machine Learning/Math/Algorithms/Functional Programming. 
Preferring projects allowing for professional growth in ML field.

Will NOT set up account in a bank company tells me. Will manage FOP myself.