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● Python experience
● Prior experience with machine learning or computer vision is a big plus, but may not be strictly necessary if you are able to learn fast and understand relevant technical documentation.

• Experience in Financial, Big Data from 1 years;
• Experience in Data Science — from 1 year;
• Python programming experience required (Data analysis libraries — NumPy, Pandas);
• Higher education — mathematics, statistics, programming, economics;
• Autonomy, orientation and responsibility for the result, system, organization, attentiveness, initiative and openness;
• Have the ability to devise and implement trading algorithms;
• Extensive knowledge on e-trading infrastructure and data specs, being able to deliver end to end solutions to the business.

• 2+ years experience with machine learning
• Great analytical skills, with expertise in analytical toolkit such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modeling, predictive analysis
• Ability to think creatively and work well both as part of a team and as an individual contributor
• Critical eye for the quality of data and strong desire to get it right
• Strong communication skills
• A pleasantly forceful personality and charismatic communication style
• English level – Upper-Intermediate

-3+ years (middle) and 5+ years (senior) of successful data science experience
-Experience with/good knowledge of NLP, pattern recognition, deep learning and other ML technologies
-Excellent programming skills, expert in Python
 - Strong experience with Tensorflow / PyTorch / Keras
-Degree in Math / Statistics / Physics

• Preferred: experience with big data processing technology stack (Spark, Hadoop, etc.)
  -A sense of urgency and ownership over the product
  -Proactive, high-energy, competitive, and creative individual
  -Driven to outperform; dedicated to self-improvement
  -Experience in a remote SCRUM team involving daily meetings, grooming, planning, etc
  -English level: Intermediate or higher

M.Sc. (with thesis) or Ph.D. in Computer Science, Mathematics, Physics or related field
Programming experience in Python/Matlab
Experience of 2+ years in data science working in a production environment
Strong English and communication skills (both speech and writing)
Highly motivated and positive-attituded person
Team player
Experience with agile development methodology
Excellent English verbal and written communication skills
Outstanding communication skills

MSc degree in Data Science, Statistics, Math, Physics, Engineering, or a similar relevant subject
3+ years of hands-on experience as Data Scientist
Experience in SQL, Python and spark
Statistical modeling experience, analytical skills and engineering skills
Ability to quickly learn new technologies, frameworks, and algorithms
We are looking for people willing to own their projects, to take risks and to go further than what the users are asking.

• hands-on experience with developing, evaluating, and releasing computer vision algorithms into production software;
• 2+ years of experience in developing novel computer vision algorithms or similar methods based on deep learning in such topics as image recognition, geometric deep learning, object recognition using 3D spatial data
• passionate about what you do and enjoy working in a collaborative environment
• upper-intermediate+ verbal and written English level.

• Extensive experience in development of software.
• Strong experience with Python (3+ years).
• Experience with focus on common ML packages: NumPy, Pandas, Sklearn, Pyod.
• Experience working with AWS Sagemaker in production.
• English — upper intermediate.
• Russian — upper intermediate.

• A minimum of a Bachelor’s degree in a mathematical discipline such as Computer Science, Applied Statistics, Maths, Engineering, or Physics from a respected University. A Ph.D. is a bonus
• 4+ years experience in Python and good knowledge of R
• At least 4 years practical experience of univariate and multivariate statistical analysis in Python or R with large data sets (millions of records and many tens or hundreds of independent variables)
• Good experience of variable transformation and data preprocessing techniques to extract maximum predictive power such as binning, piecewise linear regression, non-linear function transforms, etc.
• Excellent practical knowledge of multi-variate techniques such as Logistic Regression, Decision Trees, Random Forest, Naive Bayes, Clustering, etc. and a good grasp of the strengths and weaknesses of specific approaches
• Strong communication skills