Job Description

Pay Rate: $20.00 to a maximum of $25.00 Per Hour.

Position Purpose:

A Data Science Intern assists with analyzing large data sets to derive actionable insights and supports the development of machine learning models, while gaining hands-on experience in applying data science techniques in a real-world business context.

Student Exploration and Experience Development (SEED) is a 12-week internship opportunity at Veolia for students to gain hands-on experience in sustainability and ecological transformation. They will work on real-world projects, receive mentorship from industry professionals, and participate in workshops and networking events. The program aims to nurture talent, promote innovation, and foster meaningful connections between students and industry professionals. Overall, the SEED program provides students with the skills, knowledge, and connections needed to make a positive impact in the industry.

Program Dates: June 2, 2025 to August 22, 2025.

Primary Duties/Responsibilities:

• Analyze and interpret complex datasets to extract meaningful insights, aiding in data-driven decision making.
• Develop and implement machine learning models and algorithms to solve specific business problems, enhancing operational efficiency.
• Clean, preprocess, and validate data to ensure accuracy, completeness, and uniformity for effective analysis.
• Collaborate with cross-functional teams to understand business needs and provide data-driven recommendations and solutions.
• Prepare and present reports on findings and model outcomes to both technical and non-technical stakeholders, clearly communicating insights and implications.

Qualifications

Education/Experience/Background:

• MS degree in Computer Science or computer related field from an accredited institution.

Knowledge/Skills/Abilities:

Skills:

• Experience developing with Python.
• Experience with SQL development.
• Good experience with Git.
• Understanding of machine learning algorithms including both supervised (like linear regression, decision trees) and unsupervised learning (like clustering, principal component analysis).
• Strong foundation in statistics and mathematics, essential for understanding data distributions, hypothesis testing, and the mathematical underpinnings of machine learning algorithms.
• Skills in cleaning, manipulating, and preprocessing data using tools and techniques to handle missing values, outliers, and data transformation.
• Proficiency in data visualization tools (like Matplotlib, Seaborn, Plotly in Python) to present data findings effectively.

Abilities:

• Embrace mentorship through design sessions, code reviews, and community building.
• Strong analytical and problem-solving skills, with the ability to work with large data sets and derive insights.
• Ability to translate real-world problems into analytical questions and devise data-driven solutions.
• Capabilities in conducting statistical tests and experiments to derive insights and validate models.
• The ability to critically evaluate data sources, models, and outcomes, considering biases and assumptions.
• Good verbal and written communication skills, as the role may involve presenting findings and collaborating with team members.
• A keen interest in data science and machine learning, with a willingness to continuously learn and stay updated with industry trends and technologies.

Physical Requirements:

• Hybrid mode (3 days a week in the office).

Additional Information

We are an Equal Opportunity Employer! All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, subject to applicable law.