Alex Tselikov

• Managing a diverse team of data scientists & engineers. Mentoring, running team routines and performance reviews, developing and improving an internal career framework. • Building external teams of data scientists for clients from scratch. Setting up a technical strategy for teams according to the project’s needs. Stakeholder’s management. • Technical leading for data engineering and machine learning projects, prototyping and building products at scale.

Building a high-load data processing pipeline (up to 45 million records daily) for the 3rd world-largest car manufacturer. Cloud computing, data storing and monitoring. Analytic and machine learning use-case implementation: geodata analysis, predictive maintenance, clustering. Technologies: Azure/AWS, python, Docker, Hadoop, Spark, Streaming, supervised/unsupervised ML.

Worked on various machine learning products in an agile environment for telco (churn prevention, customer segmentation), bank scoring (the probability of customer's default) and fintech (customer's propensity for credit). Prototyping and deploying data pipelines into a large-scale production environment (60M of clients). Chat-bot developing for contact center automation (DL, NLP). Technologies: Classical ML, Deep Learning, distributed systems (Spark, Hive, Hadoop).

BI portal and KPI dashboards development, building data processing pipelines and visualizations. Billing systems and process automatization DevOps.

Ph.D. Thesis Title: "Creating an analytical decision support system in the field of municipal healthcare"