ML Engineer/ Data Scientist

Hybrid in Newyork City

Full time role

Interview- Video

Salary- $150,000 to $225,000+ Benefits

We are seeking Machine Learning Engineer / Data Scientist to join our Client's AI, Data & Operations team in New York.

In this role, you will develop and deploy machine learning models focused on time series analysis

and forecasting, working with complex datasets across multiple sources. You will play a key role in designing

and implementing scalable cloud-based solutions on Azure, collaborating with cross-functional teams to

drive data-driven insights in real estate and financial analytics.

This position requires a blend of expertise in machine learning, data engineering, and cloud infrastructure,

along with a strong analytical mindset to optimize forecasting models and deliver actionable intelligence.

Key Responsibilities

• Machine Learning Development: Design, build, and deploy predictive models, focusing on time

series forecasting, anomaly detection, and trend analysis.

• Data Engineering & ETL: Work with diverse data sources, performing extraction, transformation,

and loading (ETL) using SQL and Python.

• Cloud Deployment: Implement scalable solutions using Azure ML, Data Factory, and Application

Insights for monitoring and deployment.

• Exploratory Data Analysis (EDA): Conduct feature engineering and model validation to enhance

performance and interpretability.

• Cross-Functional Collaboration: Work closely with business stakeholders, engineers, and domain

experts to apply machine learning in real estate analytics.

• Performance Optimization: Continuously improve forecasting accuracy, model efficiency, and

computational scalability.

• Real Estate Analytics: Apply machine learning techniques to market trends, asset valuation,

leasing activity, and risk assessment in the real estate domain.

Basic Qualifications

• 4+ years of experience in machine learning, data science, or AI roles.

• Strong programming skills in Python and experience with ML frameworks (TensorFlow,

PyTorch, Scikit-learn, XGBoost, etc.).

• Experience with time series forecasting models (ARIMA, Prophet, LSTMs, etc.).

• Proficiency in SQL for querying and managing relational databases.

• Experience working with Azure cloud services, particularly Azure ML, Data Factory, and

Application Insights.

• Hands-on experience in data preprocessing, feature engineering, and model evaluation.

• Ability to interpret and communicate model results to both technical and non-technical

stakeholders.

Preferred Qualifications

• Experience with big data technologies (Spark, Databricks, Snowflake).

• Knowledge of MLOps and deployment of machine learning models in production environments.

• Prior exposure to real estate analytics or a strong willingness to learn.

• Experience with financial modeling, risk assessment, or commercial real estate data.

• Cloud certification in Azure AI/ML or similar.