Data Science - Intern

Position Summary: 

The EDAP team is an internal data team focused on delivering innovative data solutions across various business domains. We aim in turning data into actionable insights, enabling smarter internal workflows, and contributing significantly to the operational excellence of the company. The ideal candidate will have a passion for data, technology, and machine learning, with a willingness to learn and contribute to our ongoing projects. This internship offers the opportunity to gain hands-on experience in data engineering and to contribute to exciting machine learning initiatives. 

Responsibilities:

• Work closely with the team to maintain, synchronize, wrangle, and migrate data across hybrid environments.
• Assist in the development and deployment of machine learning models.
• Contribute to data exploration, analysis, and insights generation.
• Participate in technical discussions, provide feedback on requirements, and collaborate on solution design.
• Complete all other duties as assigned by manager.
• Represent the company professionally in all internal and external interactions and communications.
• Adhere to safety standards and help promote a safe working environment.
• Adhere to and promote the Mission, Vision, and Values of Stanley Martin Homes

Position Standards:

• Experience with Python libraries such as NumPy, Pandas, SciPy, and scikit-learn.
• Understanding of relational and non-relational databases and experience handling various file formats (JSON, Parquet, CSV, Text).
• Knowledge of machine learning techniques and predictive modeling.
• Basic familiarity with cloud platforms (AWS, Azure, GCP) and version control tools (Git, GitHub, Azure DevOps).
• Exposure to ETL/ELT data pipeline development.
• Team Player
• Attention to Detail
• Knowledge of MS Office, MS Teams
• Organizational Skills
• Positive Attitude
• Self-Starter
• Strong Communication Skills (written and verbal)

Position Requirements:

• Currently pursuing or recently completed a degree in Computer Science, Mathematics, or a related field.
• Proficiency in programming languages like Python, R, or Scala.
• Familiarity with databases such as BigQuery, Snowflake, SQL Server, along with an understanding of data structures.
• Exposure to data science methodologies, machine learning algorithms, and ETL/ELT workflows.
• Strong analytical and problem-solving skills.
• Effective communication, collaboration, and teamwork abilities.
• Detail-oriented, self-motivated, and eager to troubleshoot and learn new technologies.
• Ability to work both independently and in a team environment.