Position: Data Scientist (CyVers)
Company: SD Solutions
Experience required: 5y
Category: Data Science
English level: upper
Published: 2022-10-01T00:00:00+03:00

**What are we doing?**

CyVers is a DeFi & Blockchain security company that provides cryptocurrency attack detection in real-time using cutting-edge geometric anomaly detection. CyVers analyzes business off-chain and blockchain on-chain data and defines profiles of typical behaviour for crypto users. This activity enables the identification of anomalies in behaviour, a multiplicity of which may indicate malicious activity by hackers. CyVers’ Security Operation Platform empowers security, compliance, fraud, and risk teams to automatically detect and respond to incidents that matter across the entire crypto attack surfaces.

**What will you do with us?**

- Selecting features, building and optimizing classifiers using machine learning techniques.
- Data mining using state-of-the-art methods.
- Extending the company’s data with third party sources of information when needed.
- Enhancing data collection procedures to include information that is relevant for building analytic systems.
- Processing, cleansing, and verifying the integrity of data used for analysis.
- Doing ad-hoc analysis and presenting results in a clear manner.
- Creating automated anomaly detection systems and constant tracking of its performance.

**What hard skills do we need?**

- Strong experience working as Data Science/ Data Engineer.
- Experience with common data science toolkits, such as TPOT, Python, Weka, NumPy, MatLab, etc.
- Experience with data visualization tools, such as D3.js, GGplot, etc.
- Proficiency in using query languages such as SQL, Hive, Pig.
- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase.
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Good scripting and programming skills.
- Data-oriented personality.

**What soft skills do we appreciate? **
- Great communication skills.