Senior Data Scientist

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Job Responsibilities: 1. Data Aggregation & Reporting – Coordinate data aggregation and generate reports using business intelligence tools to support strategic decision-making. 2. Data Analysis & Insights – Conduct ad-hoc and strategic reviews of structured and unstructured data related to global real estate markets, financial assets, and operational performance. 3. Data Engineering & Pipelines – Assist in building scalable data pipelines and architectures to streamline data collection, cleansing, transformation, and storage for analytical insights. 4. Statistical Analysis & Modeling – Define key data requirements, conduct statistical analyses (regression modeling, time-series analysis, hypothesis testing), and identify causal relationships among key business and financial metrics. 5. Machine Learning & AI Implementation – Design, build, and deploy ML models for various financial applications, including: a. Risk assessment & portfolio optimization b. Customer segmentation & profitability maximization c. Anomaly detection & investment forecasting 6. Forecasting & Predictive Analytics – Develop and operationalize forecasting models for financial markets, risk exposure, asset valuation, and economic trends using time-series analysis, econometric techniques, and deep learning. 7. Optimization & Business Performance – Apply optimization methods, Monte Carlo simulations, and quantitative modeling to enhance financial performance, capital allocation, and strategic investment decisions. 8. Programming & Development – Utilize advanced programming and open-source tools to build, evaluate, and optimize predictive models, ensuring scalability and efficiency in production environments. Qualifications: 1. Location & Language – The candidate must be U.S.-based with Native or Bilingual English proficiency. 2. Technical Expertise – Strong background in AI, ML, data science, statistics, and mathematics applied to financial services and real estate analytics. 3. Data Science Experience – Minimum 5+ years of full-time experience as a Data Scientist, specializing in complex datasets and predictive modeling. Experience in financial services, investment banking (IB), wealth management, risk management, or real estate is preferred but not required. 4.Education – a. Master’s degree in Data Science, Mathematics, Statistics, Computer Science, Computational and Mathematical Engineering, or a related field from a U.S.-based accredited university +5 years of industry experience, OR b. Ph.D. (preferred) in one of these fields + 2 years of industry experience. 5. Machine Learning & Deep Learning – Hands-on experience with TensorFlow, PyTorch, Scikit-Learn, and modern deep learning architectures. 6. Programming & Data Tools – Strong coding proficiency in Python, R, or Java, along with experience in SQL, Power BI, Excel, and relevant data science libraries. 7. Big Data & Cloud Technologies – Familiarity with distributed computing, AWS, GCP, or Azure, and frameworks like Spark, Hadoop, or Dask is a plus. 8. MLOps & Deployment – Experience with model versioning, deployment pipelines (CI/CD), and ML model monitoring in production environments. 9. Statistical & Mathematical Software – Expertise with R, SAS, Matlab, and advanced data visualization techniques. 10. The candidate must be highly responsive, collaborative, and strictly adhere to deadlines.

Keyword: cloud

Contractor Tier: Hourly: $80.00 - $250.00

Price: $165.0