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Quantum is a global technology partner delivering insightful & data-driven software products. In-depth expertise in Big data & emerging technologies combined with profound software engineering skills allows us to think outside the box in tackling unique business challenges.
3 червня 2022

Data Scientist (вакансія неактивна)

за кордоном, віддалено

Life with Quantum is more than just project delivery. See for yourself.

Quantum is a data analytics and software engineering company with an international presence and R&D center. We are looking for progressive solutions to real problems, leaving the comfort zone. This allows us to remain the leaders of the Big Data market.

You will be a part of the company and surrounded by experts who are ready to move forward professionally.

About the project

Our client is a digital transformation, cognitive computing, artificial intelligence software company. Their product is a highly scalable and customizable platform that serves as an AI Operating system. This system is used for a wide range of capabilities such as business intelligence, decision making, forecasting, and situational awareness. The product also contains cognitive computing applications configured for specific industries and business functions.

Must have skills

  • 4+ years of industry and research experience in developing ML products;
  • Great written and verbal communication skills, with prior experience explaining assumptions, conclusions, and methodology to both internal and external customers;
  • Ability to frame business requirements into ML problems that you enjoy solving;
  • A strong predilection for good software and the processes that make it;
  • Mathematical foundation including: linear algebra, vector calculus, probability, and statistics. Experience implementing this math effectively in software (e.g. Python, numpy);
  • Strong foundation in machine learning & deep learning concepts including: supervised and unsupervised learning, transfer learning, ensembling, classification, regression, clustering, bias & variance, regularization, overfitting & underfitting, Logistic & Linear regressions, Decision Trees, MLP, RNNs;
  • Strong foundation in natural language processing concepts including: bag-of-words & TF-IDF, n-grams, word & text embedding, NER, transformers, text classification & similarity;
  • Proficiency in Python and PyData stack (numpy, scipy, pandas, scikit-learn);
  • Fluency with popular NLP libraries (spaCy, NLTK, transformers);
  • Hands-on experience with Deep Learning frameworks such as PyTorch;
  • Experience working in a Linux environment;
  • Basic Git knowledge: creating and merging branches, cherry-picking commits, examining the diff between two hashes;
  • More advanced Git usage is a plus, particularly: development on feature-specific branches, squashing and rebasing commits, and breaking large changes into small, easily-digestible diffs;
  • Experience with SQL;
  • Understanding of algorithm complexity and performance implications;
  • Knowledge of classical data structures and algorithms.

Nice to have skills

  • Degree in related field (Machine Learning, Data Science, Mathematics, Statistics, Computer Science);
  • Familiarity with Knowledge Engineering, Graph technology, Knowledge Graphs, Graph Databases;
  • Machine Learning on graphs;
  • AWS, AWS SageMaker;
  • Kaggle experience.

You will be responsible for

  • Work closely with Team Leader, Product Managers, fellow Data Scientists and ML Engineers to frame Machine Learning problems within the business context;
  • Provide support to more junior ML engineers and Data Scientists in the team;
  • Be hands-on and involved with every stage of the ML product development cycle;
  • Assist in design and reviewing ML experiments and solutions;
  • Evaluate, justify and communicate ML models’ performance to various stakeholders;
  • Write clean and tested code that can be maintained and extended by other fellow ML engineers;
  • Contribution to research activities in ML domain inside the company.

We offer

  • Exchange of experience, professional development;
  • A strong team, a healthy atmosphere;
  • Flexible working time;
  • 20 days paid vacation;
  • Paid sick leave;
  • 8-hour working day and 5-day working week;
  • Opportunity to take part in conferences, meetups, etc. (fully or partially paid by the company);
  • Regular company events.

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