THE OPPORTUNITY
XGS (XGS.ai) is a rapidly growing developer of AI FinTech solutions for M&A and Operations. With a global presence, we work with corporate and private equity clients on complex decisions that involve strong analysis, extensive modeling, and advanced data analytics across a wide variety of industries and business functions. This role is a hybrid role for the XGS office located in Athens, Greece.
THE ROLE
This is a unique opportunity for a Principal Data Scientist who wishes to work in the intersection of a product focused and consulting services company. The primary responsibilities of the role will be to build statistical, ML, and AI software modules working alongside product managers, software engineers and designers. The new Data Scientist will also be working side-by-side with consultants and senior finance and tech executives providing principled ways of leveraging data to answer key business questions,and turn data discoveries and processes to operational capabilities.
The Data Scientist will:
- Identify business trends and problems through complex data analysis.
- Interpret results from multiple sources using a variety of techniques, ranging from simple data aggregation to complex data mining.
- Prepare data, implement data models and develop databases to support business solutions.
- Develop novel ways to help business partners achieve objectives through analysis and modelling
- Utilize machine learning to create repeatable, dynamic, and scalable models
- Identify and develop long-term Data Science processes, frameworks, tools, and standards
Qualifications and Expertise
While we’re looking for some specific experiences and skill-sets, nothing is more important than a
strong work-ethic, resilience in the face of change, and a passion for learning and creating.
Requirement
- Bachelor’s degree in Data Science, Computer Science, Engineering, Math, Statistics, Physics
or related field
- Masters in Machine Learning or Data science
- 7+ years of working experience in applying ML, Statistics, or AI
Machine Learning Experience
- Deep expertise in any of the following: Time-Series Modelling, Optimization, Pricing,
Deep Neural Networks, Natural Language Processing (NLP) or Retrieval Augmented Generation (RAG) applications
- Experience in development and deployment of Machine learning models into production-grade applications
Software and Technology Experience
- Strong Python, PySpark and SQL skills
- Experience in using version control software (Git, Azure DevOps)
Soft Skills
- Ability to define agenda for data science projects, frame business questions into analytical plans (e.g. assess data needs, prepare data and create features, develop and evaluate ML models) and execute.
- Strong communication
and presentation skills to deliver insights to senior management and ability to articulate findings in a clear, concise and visually appealing manner.
