Sr Data Scientist
ID da função
Linha de serviço
GWS Segment
Tipo de trabalho
A tempo inteiro
Áreas de interesse
Análise de Dados
Warsaw - Mazowieckie - Poland

Working at the direction of the Senior Managing Economist, this role will evaluate the quality of proprietary and third-party data, to develop machine learning algorithms to interrogate data, and to develop and implement a scaling stack to develop products for the purpose of business intelligence.


Works/leads on complex, cross-functional research or analytical projects leveraging advanced computational algorithms.

Applies the tools of modern data science using open source architecture to the analysis of CBRE's proprietary data

Leads data research efforts for product development for internal and external clients. Analysis gathered data to recommend product updates per results. Partners with D&T to drive development.

Develops custom algorithms for solving complex real estate business problems across a wealth of structured and unstructured data across multiple data sources.

Identifies and evaluates current, new, and third party data sources. Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart meters and geo-location information.

Defines data requirements and gather and validate formation, applying judgment and statistical tests.

Performs other duties as assigned.


Provides formal supervision to direct reports. Recommends staff recruitment, selection, promotion, advancement, corrective action and termination. Conducts performance appraisal and other performance discussions with individual employees. Plans and monitors appropriate staffing levels and utilization of labor, including overtime. Prepares and delivers performance appraisal for staff. Mentors and coaches team members to further develop competencies. Leads by example and models behaviors that are consistent with the company's values.


To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.


Masters or Ph.D. degree from top tier school in applied data science computer science, engineering, applied math or related degree. Minimum 4-6 years of experience in statistical analysis, data engineering, and data visualization. Consideration given to equivalent combination of education and experience.

Ph.D. in computer science or be nearing the completion of a Ph.D. preferred.


Data Scientist Certification or equivalent combination of experience and/or education.


Ability to comprehend, analyze, and interpret the most complex business documents. Ability to respond effectively to the most sensitive issues. Ability to write reports, manuals, speeches and articles using distinctive style. Ability to make effective and persuasive presentations on complex topics to employees, clients, top management and/or public groups. Ability to motivate and negotiate effectively with key employees, top management, and client groups to take desired action.


Requires knowledge of financial terms and principles. Ability to calculate intermediate figures such as percentages, discounts, and/or commissions. Conducts basic financial analysis.


Ability to solve advanced problems and deal with a variety of options in complex situations. Requires expert level analytical and quantitative skills with proven experience in developing strategic solutions for a growing matrix-based multi-industry sales environment. Draws upon the analysis of others and makes recommendations that have a direct impact on the company.


Demonstrated knowledge of R and/or Python, together with SQL.

Demonstrated knowledge of standard machine learning algorithms, based on "An Introduction to Statistical Learning" by James et. al. or similar textbook. Demonstrated knowledge of strengths, weaknesses, and real-world performance of the ML algorithms.

Demonstrated knowledge of web scrapping and data preprocessing.


Decisions made with in-depth understanding and interpretation of procedures, company policies and business practices to achieve general results. Responsible for setting department deadlines. Errors in judgment may cause long-term impact to co-workers, supervisor, department and/or line of business.