Overview
On Site
$130,000 - $150,000
Full Time
No Travel Required
Skills
Algorithms
Analytical Skill
Analytics
Artificial Intelligence
Asset Management
Business Intelligence
Cloud Computing
Computer Science
Dashboard
Data Engineering
Data Extraction
Data Quality
Data Science
Database
Decision-making
Document Processing
Evaluation
Extract
Transform
Load
FOCUS
Finance
Large Language Models (LLMs)
Leadership
Machine Learning (ML)
Management
Market Analysis
Natural Language Processing
NumPy
Optical Character Recognition
Optimization
Pandas
Prompt Engineering
Property Management
PyTorch
Python
Quality Assurance
Real-time
Reporting
SQL
Science
Snow Flake Schema
TensorFlow
Unstructured Data
Unsupervised Learning
Valuation
scikit-learn
BI
data engineer
analytics engineer
AI
ML
snowflake
nexla
OCR
NLP
LLM
ETL
scikit
cloud data warehouse
hugging face
Job Details
Our client, a real estate and asset-based lender, is looking to hire a full-time Analytics Engineer to work onsite out of their Midtown Manhattan location.
This is a dynamic team focusing on optimizing the firm's asset management operations and business intelligence (BI) capabilities. This role combines technical data engineering expertise with analytical science skills to drive data-informed decision-making across their portfolio.
Responsibilities:
- Build automated reporting systems and interactive dashboards for portfolio monitoring, including custom analyses for executive leadership, asset management, and origination
- Implement machine learning (AI) models for asset valuation, market analysis, and investment opportunity screening
- Build and optimize Snowflake databases and queries to support real-time business intelligence needs
- Design and implement quality assurance processes for data extraction, transformation, and analysis workflows
- Design and maintain scalable data pipelines in Nexla and Python to integrate property management systems, financial databases, and market data feeds into our Snowflake data warehouse
- Develop and implement OCR/NLP models to extract, validate, and classify key information from loan agreements, property reports, and other financial documents
- Create predictive models to identify asset performance trends, risks, and opportunities across the real estate portfolio, with a focus on occupancy rates and NOI metrics
- Design and optimize ETL processes to ensure data quality/consistency, with robust monitoring and alert systems
Qualifications:
- Bachelor's or Master's Degree in Computer Science, Data Science, or related field with 3-7 years of experience; additional experience may be considered in lieu of degree
- Expert-level Python programming with strong proficiency in data science libraries (pandas, numpy, scikit-learn) and ML frameworks (TensorFlow, PyTorch)
- Experience building and optimizing ETL pipelines using modern data platforms (they use Nexla) and working with Snowflake or similar cloud data warehouses
- Demonstrated experience with large language models (LLMs), prompt engineering, and NLP frameworks (e.g., Hugging Face Transformers) for document processing and information extraction
- Proficiency in data preprocessing, cleaning, and transformation techniques for both structured and unstructured data sources
- Experience with supervised and unsupervised learning algorithms, model evaluation metrics, and ML deployment in production environments
- Advanced SQL expertise, particularly with Snowflake, including optimization and security best practices
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