The Amherst Group of companies comprise of leading real estate investment and advisory firms with a mission to transform the way real estate is owned, financed and managed. Amherst leverages its proprietary data, analytics, technology, and decades of experience to seek solutions for a fragmented, slow-to-evolve real estate ecosystem and to materially improve the experience for residents, buyers, sellers, communities, and investors. Today Amherst has over 1000 employees and $14.1 billion in assets under management.
Over the past decade, Amherst has scaled its platform to become one of the largest operators of single-family assets and has acquired, renovated, and leased more than 46,000 homes across 32 markets in the U.S. The firm delivers customized, stabilized cash-flowing portfolios of assets to its investors, wrapped in all the ongoing services required to manage, own, and finance the asset including property management, portfolio management, and a full capital markets team. In addition to its single-family rental platform, Amherst’s debt business pursues two distinct credit strategies in mortgage-backed securities and commercial real estate lending. Over its 25-year history, Amherst has developed a deep bench of research and technology talent, and leverages data and analytics at every stage in the asset lifecycle to improve operations and preserve long-term value for our investors and the more than 188,000 residents the firm has served.
Amherst is looking for a skilled Data Analyst with expertise in working with large data sets, leveraging AI (Artificial Intelligence) and ML (Machine Learning) techniques to extract insights, build predictive models, and deliver actionable business solutions. The ideal candidate will possess strong analytical skills, technical proficiency, and a passion for working with data to solve complex problems.
Job Description (Primary Responsibilities)
Data Collection and Preparation:
Collect, clean, and preprocess large volumes of structured and unstructured data from multiple sources.
Develop and maintain data pipelines to ensure the accurate and efficient processing of data.
Handle data inconsistencies, missing values, and outliers, ensuring high-quality, usable datasets for analysis.
Exploratory Data Analysis (EDA):
Perform detailed exploratory data analysis (EDA) to understand data patterns, trends, and relationships.
Visualize data using tools such as Tableau or Power BI to identify key insights and drive decision-making.
AI and Machine Learning Model Development:
Apply AI and machine learning algorithms (e.g., classification, regression, clustering, deep learning) to build predictive and prescriptive models.
Train, tune, and evaluate machine learning models to optimize their performance.
Automate model deployment and update processes for continuous improvement in accuracy and efficiency.
Advanced Analytics:
Use statistical methods and machine learning techniques to forecast trends, identify anomalies, and detect patterns in large data sets.
Apply natural language processing (NLP) and computer vision techniques for text and image data analysis when needed.
Data Visualization and Reporting:
Communicate findings clearly through visualizations and reports to stakeholders across the organization.
Present complex data insights in an accessible and actionable format for both technical and non-technical audiences.
Collaboration and Communication:
Work closely with cross-functional teams to understand business needs and objectives.
Provide analytical support to business stakeholders by offering data-driven insights and recommendations.
Continuous Improvement:
Stay updated on the latest trends in AI/ML technologies and data analytics.
Continuously evaluate and implement new techniques to improve the quality and efficiency of analysis.
Explore new ways to automate repetitive tasks and improve business operations through data-driven solutions.
Desired Skills/Qualifications:
Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a quantitative related field.
Experience: 2-5 years of experience in data analysis, data science, or machine learning roles, with hands-on experience in managing and analyzing large datasets.
Skills:
Proficiency in Python, R, or similar programming languages for data analysis and machine learning.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit- learn.
Familiarity with AI techniques, including deep learning, reinforcement learning, and NLP.
Strong knowledge of SQL for querying large data sets.
Expertise in data visualization tools (e.g., Tableau, Power BI).
Experience with big data platforms and tools (e.g., Hadoop, Spark) is a plus.
Familiarity with cloud platforms (AWS, GCP, Azure) for data storage and processing.
Soft Skills:
Strong problem-solving and critical-thinking abilities.
Excellent communication and presentation skills.
Ability to work independently and as part of a team.
Attention to detail and the ability to work with complex data sets.
Preferred Qualifications:
Experience with deploying machine learning models to production environments.
Knowledge of advanced analytics techniques such as time series forecasting, anomaly detection, or reinforcement learning.
Experience in a real estate industry is a plus.
Our full-time employee benefits include:
