Raman DATA SCIENTIST/ MACHINE LEARNING ENGINEER
Summary
- 10+ years experience working in the IT industry;
- 8+ years experience working with Python;
- Strong skills with SQL;
- Good abilities working with R and C++;
- Deep knowledge of AWS;
- Experience working with Kubernetes (K8s), and Grafana;
- Strong abilities with Apache Kafka, Apache Spark/PySpark, and Apache Airflow;
- Experience working with Amazon S3, Athena, EMR, Redshift;
- Specialised in Data Science and Data Analysis;
- Work experience as a team leader;
- Upper-Intermediate English.
Experience
Team lead of Machine Learning Engineers, Personalized Virtual Player Assistant
2021 - 2023
Responsibilities: I led a team of machine learning engineers to develop a virtual assistant for Softcorp company's players based on TensorFlow, PyTorch, and OpenAI API. I defined the project strategy and key milestones, ensuring the timely implementation of critical features. Under my leadership, the assistant was successfully developed and deployed, offering verbal (textual and voice) recommendations to players. Throughout the process, a scalable and robust infrastructure was implemented using Kubernetes and Kubeflow. I closely collaborated with designers and the development team to ensure an intuitive and comfortable user interaction.
Technologies: Kubernetes, Kubeflow, OpenAI API, Autogen, Python, Rasa NLU, TensorFlow, PyTorch, NLTK, NumPy, BERT etc.
Senior Machine Learning Engineer, Contextual Troubleshooting Recommendations
2020 – 2021
Responsibilities: Designed and developed an automated contextual search engine for providing troubleshooting recommendations. Utilized natural language understanding techniques to comprehend user queries and extract relevant information. Built an efficient contextual search engine that delivered accurate troubleshooting recommendations in real-time. Integrated the system with Elasticsearch, ensuring fast and precise search capabilities. Incorporated advanced BERT-based models to enhance query understanding and relevance.
Technologies: AWS, Clickhouse, Grafana, Rasa NLU, Python, Elasticsearch, NLTK, Spacy, ONNX and BERT.
IT-academy
2018 – 2020
Responsibilities: The coach in the IT academy in Data Science. My responsibilities include conducting theoretical and practical classes, preparing and training students, as well as protecting their diploma projects. All graduates of my classes are currently working in the IT field.
Technologies: Python, Tensorflow, PyTorch, PySpark, Keras etc.
Machine Learning Engineer, Spare Parts Extraction and Database Integration
2018 – 2020
Responsibilities: Machine learning engineer in the GFAIVE - a full-stack data engineering and AI consulting firm. Designed and implemented machine learning models for classifying articles based on their content. Preprocessed and cleaned article data to ensure high-quality input for the models. Achieved an accuracy of 89% in categorizing articles into relevant contexts. Developed a scalable and efficient pipeline for automated article classification. Collaborated with the development team to seamlessly integrate the classification system into the site context-filling process. Significantly improved the site context-filling process by reducing manual effort and enhancing accuracy
Technologies: AWS, S3, SageMaker, EC2, Python, BeautifulSoup, Spacy, NLTK, Pandas, TensorFlow.
Head of the Geospatial Information Research Department in the Military Research Institute.
2011 – 2018
Responsibilities: Head of the Geospatial Information Research Department in the Research Institute. Responsibilities: Conduct research aimed at automating the receipt of geospatial data from a variety of sources. Create digital information about the surface of the Earth, navigational and temporary provision of weapons systems. Map digitization time decreased by 30%
Technologies: C++, OpenCV, Open Street Map, ArcGis.
Education
PhD
Weapons theory, military-technical policy
2012/2015
Military Academy
Master of Technical Sciences
2010/2011
Military Academy
Radio and Satellite Telecommunications Engineer
2000/2004