Data Analyst

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Amherst

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Real Estate • Finance • Technology

Amherst is a vertically integrated real estate investment, development, and operating platform that seeks to revolutionize some of the most fragmented and inefficient sectors of U. S. real estate, including single-family residential, mortgage-backed securities, and commercial real estate. Utilizing proprietary technology, extensive expertise, and a dynamic, collaborative approach, Amherst aims to create innovative solutions that transform the real estate industry from end-to-end, providing long-term value to investors, residents, and communities. The company focuses on efficiency through in-house services, ensuring each asset benefits from economies of scale. Amherst leverages decades of data-driven insights to anticipate market trends and develop strategies that unlock value, managing over $18. 5 billion in assets and over 45,000 homes across 32 U. S. markets.

1001 - 5000 employees

🏠 Real Estate

💸 Finance

📋 Description

• 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. • 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. • 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. • 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. • 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. • 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. • Stay updated on the latest trends in AI/ML technologies and data analytics.

🎯 Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a quantitative related field. • 2-5 years of experience in data analysis, data science, or machine learning roles, with hands-on experience in managing and analyzing large datasets. • 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.

🏖️ Benefits

• A competitive and comprehensive benefits package