Data Scientist

About us

Faraday Norton is a privately owned investment group, operating in the real estate, energy, and other business sectors, in Greece and abroad.

Our Company, a subsidiary of Faraday Norton, is a stealth-mode startup in the Web3 space. Our focus is on developing an innovative investment platform designed to elevate the success of both retail and institutional investors. Founded and led by three proven & and experienced founders with a track record of building and scaling successful ventures, our company offers a unique opportunity to be at the forefront of a transformative project with substantial growth potential.

About the Role:

Are you passionate about leveraging data to make smarter investment decisions? We are seeking a dynamic and driven Data Scientist to join our Business Development & Analytics team. In this role, you will use advanced machine learning and data science techniques, particularly stochastic models, to model revenue probability and uncover actionable insights that enhance business decisions and customer experiences across our product portfolio.

Key Responsibilities:

• Automate data sourcing processes and identification of new data process improvement opportunities.

• Develop and automate customized queries, reports, and visualization dashboards for management and various stakeholders using tools like Hive, Presto, SQL Server, and Tableau.

• Analyze large datasets to identify trends, patterns, and actionable insights that support smarter investment decisions.

• Apply statistical modeling and machine learning techniques to model revenue probability, optimize investment execution, and enhance strategy evaluation and risk management.

• Collaborate with investment stakeholders to define key metrics, goals, and objectives, and to generate systematic KPIs related to the group’s investment portfolio.

• Analyze diverse data from various property types and locations to identify investment opportunities and provide recommendations to improve portfolio yields and asset allocation.

• Drive analytics to uncover insights and enhance operational efficiency in investment decisions.

Qualifications:

• An undergraduate or master's degree in a quantitative field such as mathematics, engineering, statistics, finance, or similar.

• 1-3 years of work experience involving quantitative data analysis and complex problem solving.

• Possess a strong understanding of statistical and modeling techniques, including attribution methods and measurement mechanisms crucial for financial modeling and investment strategy evaluation.

• Familiarity with machine learning algorithms and techniques for predictive analytics, particularly in real estate, which would enhance investment analysis capabilities.

• Proficiency in SQL, Python or R, and familiarity with Excel, Tableau, Mode, or other visualization software. Experience querying multi-terabyte-sized noisy datasets, such as pricing data.

• Experience with tools like DBT, Snowflake, Looker, Tableau, Airflow, or Fivetran, tailored for robust data handling and advanced analytics in the investment sector.

• Experience in developing and automating management-level reports and visualizations.

• Familiarity with ETL pipelines, scheduling, and productionalization is a plus.

• Excellent critical thinking and time management skills.

• Strong written, verbal, and visual communication skills, with the ability to effectively communicate complex analytical findings to a diverse range of stakeholders.