Position: Data Scientist
Category: Python
Experience: 1 years | English: fluent

1. Graduated from BSc Molecular Biology and MRes Drug design with a computational specialisation at UCL. 
2. Worked on my own project 'Computational analysis and prediction of protein targets druggability'
In this work I performed a deep analysis of all known targets and their drugs, developed a machine learning algorithm to predict how likely a potential target is to be drugged by orally bioavailable molecules. During this project I developed my Python programming skills and data analysis. I worked with big data from biological databases, such as ChEMBL, DrugBank, PDB, UniProt, Pfam and SCOP. After data preparation, I exploited machine learning algorithms like random forest and linear regression to develop a predictive model.
3. Acquired 'Introduction to Data Science' specialisation taught by IBM
Obtaining this specialisation I have learnt data science methodologies, had an experience of working with various tools like R studio, Jupiter lab, IBM cloud and others. Gained a skill of analysing real datasets using python and SQL.
1. Consultant at First Bridge (currant Part-time job)
First Bridge is an R&D company that develops technology for various fields. My current role is to consult the company regarding potential collaborations with biotech startups. My multidisciplinary background in both bilgy and computational technologies allowed me to evaluate how a technological know-how developed by First Bridge can be implemented to improve biotech products of collaborators. Besides the technological knowledge, this position also requires deep understanding of business aspects of the problems, as well as creative thinking to come up with economically beneficial solutions.

2. Boot camp alumnus at AION Labs
AION Labs in collaboration with BioMed X created a startup incubator that was recruiting potential founders for the project ''De Novo Computational Design of Therapeutic Antibodies'. All applicants had to submit an original proposal how fully automated antibody design can become possible. I was selected as one of the top 15 applicants to participate in the boot camp, being the youngest participant. This camp was an extremely valuable experience, where I worked with professionals from various backgrounds. The main challenge was to propose a mechanism of a machine learning based platform that would be capable of antibody design. This goal was to be achieved in 5 days working in teams, so this experience extremely developed my skills in teamwork, communication, presentation and working under significant pressure. The challenge required us to come up with original, new state of the art ideas with a solid scientific grounding. Our proposals were evaluated by the representatives of the leaders in Pharma industry, including Pfizer, AstraZeneca, Merck and Teva. My team and I performed at a high level and I was a valuable team member, as my broad knowledge of both biological and computational drug design approaches was very useful. After this camp I have a much broader understanding of currant approaches in antibody design and improved significantly in my creative thinking while proposing new potential approaches to currently unsolved problems.