Data Science Team Leader
Опубліковано 20 липня 2021
Напрямки:
Data Engineering
Data Science & AI
Чим Ви будете займатись Обов'язки
- Work closely with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context;
- Provide mentorship to other ML engineers and Data Scientists in the team;
- Be hands-on and involved with every stage of the ML product development cycle;
- Design, extend and review 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;
Що ви маєте вміти Обов'язково
- 2+ years as Team Leader, working with Agile methodologies;
- 5+ years of industry and research experience in developing machine learning products;
- Excellent 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 Machine Learning 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 with SQL;
- Understanding of algorithm complexity and performance implications;
- Knowledge of classical data structures and algorithms;
- Upper-Intermediate level of English.
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