Data Scientist

About Burgiss Group:
Burgiss is a global, market-leading provider of data and analytics solutions for investors. With over 30 years of expertise in alternative investments, we offer unrivaled data, analytics, and transparency that enable asset owners, asset managers, and financial intermediaries to evaluate and manage complex portfolios. Burgiss’ solutions serve 1,000+ clients in more than 30 countries, delivering data that represents over $15 trillion in assets. 
With offices throughout the Americas, EMEA, and Asia Pacific, we leverage our network and expertise so that we can service our clients by focusing on their varying needs across regions.
About the role:

We are looking for an experienced Python programmer with deep Natural Language Processing expertise and, less critically, Computer Vision model deployment and fine-tuning experience.
Data Scientist is responsible for identifying valuable data sources and automating collection processes; data wrangling; analyzing data to discover trends and patterns; designing, developing, fine-tuning and re-training ML and deep learning (DL) systems; conducting machine learning tests and experiments; implementing appropriate ML (and, when applicable, rules-based) algorithms; proposing solutions and strategies to business challenges and collaborating with engineering and product development teams.
Responsibilities:
• Identify valuable data sources and automate collection processes; undertake data wrangling.
• Present information using data visualization techniques.
• Design and build efficient self-learning applications and artificial intelligence products in collaboration with Data Operations, Engineering and Product Management teams.
• Combine models through ensemble modeling.
• Study and transform data science prototypes.
• Research and implement appropriate ML architectures, algorithms and tools.
• Produce project outcomes and isolate the issues that need to be resolved, to make programs more effective.
• Select appropriate datasets and data representation methods.
• Run machine learning tests and experiments.
• Perform self-audit and other quality assurance functions.
• Perform statistical analyses and fine-tuning using test results.
• Train and retrain systems when necessary.
• Extend existing ML libraries and frameworks.
• Research and implement best practices to improve the existing machine learning infrastructure.
• Keep abreast of developments in the field.
• Build algorithms based on statistical modeling procedures and build and maintain scalable machine learning solutions in production.
• Use data modeling and evaluation strategy to find patterns and predict unseen instances.
• Communicate and explain complex processes to people who are not programming experts.
• Liaise with stakeholders to analyze business problems, clarify requirements, and define the scope of the resolution needed.
• Analyze large, complex datasets to extract insights and decide on the appropriate technique.
• Collaborate with data engineers to build data and model pipelines.
• Meet personal and team deadlines through time management and collaboration with team members.
Required Qualifications & Skills:
• Minimum of two years of a proven work-related or academic experience in data science and machine learning.
• Ability to write robust code in Python. Knowledge of R and Java is preferred but not required; familiarity with machine learning frameworks (such as PyTorch, Hugging Face, TensorFlow and Keras) and libraries (e.g., scikit-learn).
• Private equity and real estate experience preferred but not required.
• Understanding of data structures, data modeling and software (ML and rules-based) architectures; outstanding analytical and problem-solving skills.
• Deep knowledge of mathematics, probability, statistics, and algorithms.
• Ability to prioritize tasks, work on multiple assignments simultaneously, and manage rapidly changing assignments in a team environment.
• Workflow coordination experience.
• Strong time management and critical thinking skills Highly self-motivated with strong attention to detail.
• Excellent interpersonal and communication skills (written and verbal). A desire to work in a team environment, often under pressure. Demonstrates high standards of ethics and fairness.
• Advanced MS Excel and Word skills a plus.
• Data Science and/or AI-related university degree is preferred but not required.
• CAIA/CFA certification is preferred but not required.
Life at Burgiss
At Burgiss, you can expect:

Additional Health insurance (lux package with included dental) .
Life Insurance.
Sports Card (Shared cost – Employee/Company) .
Food vouchers in the amount of 200 BGN.
Employee Assistance Program (EAP) .