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À propos
Information contained in this position specification as well as any other information concerning the Company provided or verbally discussed is confidential. All materials and discussions are to be utilized for the sole purpose of a candidate’s personal review of the career opportunity.
The Company is a privately-held and vertically-integrated real estate company that develops, owns, and operates a portfolio of multifamily, industrial, and mixed-use developments. With corporate offices in Atlanta, Boston, Dallas, Dubai, New York, and San Francisco, the firm is an experienced real estate private equity investor and manager supported by an integrated operating platform and has 65+ years of experience across multiple asset classes. During its 65+-year history, the Company has developed, managed or acquired over 96,000 residential units and 32.5 million square feet of commercial space in twenty-four states. The current portfolio includes over 57,000 residential units, 1 million square feet of retail and office space, and 26 million square feet of industrial space.
DATA SCIENTIST As a member of the cross-disciplined Strategic Analytics team, the Data Scientist will play a crucial role in analyzing complex datasets, uncovering valuable insights, and providing data-driven solutions to drive business growth and innovation. The data scientist will work closely with business leaders to improve operating performance and foster data-driven decision-making processes across the firm’s investment and operating verticals. Data Analysis and Modeling: Utilize statistical techniques and machine learning algorithms to analyze large and complex datasets. Apply data preprocessing, feature engineering, and predictive modeling to extract meaningful insights and develop robust models. Contribute to the solution of business challenges through innovative solutions using data-driven approaches. Data Visualization: Machine Learning Development: Support the creation and deployment of machine learning models, leveraging both traditional statistical techniques and cutting-edge algorithms. Optimize models for performance, scalability, and interpretability. Data Exploration and Cleansing: Work with in-house data engineering team to conduct exploratory data analysis to understand data characteristics, identify data quality issues, and address missing or inconsistent data. Implement data cleansing techniques and develop strategies to improve data quality and integrity. Collaborative Approach: Collaborate with data engineers, software developers, data analysts, and business stakeholders, to integrate data science solutions into existing systems and processes. Provide guidance and support to team members on best practices in data science methodologies and tools. Bachelor's degree or higher in Computer Science, Statistics, Mathematics, or a related field. ~ Proficiency in programming languages such as SQL and Python or R. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools (e.g. Power BI). Knowledge of Azure ML and Snowflake (Snowpark ML) a plus. Willingness to learn new technologies and methodologies to stay ahead in the field of data science. ~2-3 years’ experience in a data science or analytics role, applying statistical analysis and machine learning techniques to real-world problems.
The Company is prepared to offer a competitive compensation package including salary, bonus and other benefits.
Compétences linguistiques
- English
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