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Data Science Intern

3 weeks ago

Toronto, Ontario, Canada Arcadis Full time

Arcadis is the world's leading company delivering sustainable design, engineering, and consultancy solutions for natural and built assets.

We are more than 36,000 people, in over 70 countries, dedicated to improving quality of life. Everyone has an important role to play. With the power of many curious minds, together we can solve the world's most complex challenges and deliver more impact together.

Role description:
We are looking for an enthusiastic Bachelor's or Master's student to join our data and AI team as a Data Science Intern. In this role, you will help develop and optimize data-driven solutions, build machine learning models, and deploy them to production. You will work closely with data engineers, machine learning engineers, product teams, and stakeholders to transform data into actionable insights and intelligent systems.

Role accountabilities:

  • Data Preparation & Analysis: Collect, clean, and pre-process structured and unstructured data for modeling and analysis, Perform exploratory data analysis to identify patterns, trends, and anomalies.
  • Model Development & Evaluation: Design, implement, and train machine learning models for predictive and classification tasks. Evaluate model performance using appropriate metrics and optimize for accuracy and efficiency.
  • Engineering & Deployment: Collaborate with data engineers and machine learning engineers to integrate models into production environments. Contribute to building scalable pipelines for data ingestion, feature engineering, and model deployment.
  • Collaboration & Documentation: Work closely with product teams to understand business requirements and translate them into technical solutions. Document processes, models, and findings clearly for both technical and non-technical audiences.

Qualifications & Experience:

  • Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, Statistics, Mathematics, or a related field.
  • Strong interest in data science and AI, with a willingness to explore emerging tools and technologies.
  • Eagerness to learn and adapt quickly in a fast-evolving AI landscape.
  • Basic understanding of machine learning concepts and data science fundamentals (e.g., data preprocessing, model basics, evaluation metrics).
  • Familiarity with Python and common data science libraries.
  • Ability to work collaboratively and share learnings with the team.
  • Good communication and collaboration skills.

Why Arcadis?

We can only achieve our goals when everyone is empowered to be their best. We believe everyone's contribution matters. It's why we are pioneering a skills-based approach, where you can harness your unique experience and expertise to carve your career path and maximize the impact we can make together.

You'll do meaningful work, and no matter what role, you'll be helping to deliver sustainable solutions for a more prosperous planet. Make your mark, on your career, your colleagues, your clients, your life and the world around you.

Together, we can create a lasting legacy.

Join Arcadis. Create a Legacy.

Our Commitment to Equality, Diversity, Inclusion & Belonging

We want you to be able to bring your best self to work every day which is why we take equality and inclusion seriously and hold ourselves to account for our actions. Our ambition is to be an employer of choice and provide a great place to work for all our people. We are an equal opportunity and affirmative action employer. Women, minorities, people with disabilities and veterans are strongly encouraged to apply. We are dedicated to a policy of non-discrimination in employment on any basis including race, creed, color, religion, national origin, sex, age, disability, marital status, sexual orientation, gender identity, citizenship status, disability, veteran status, or any other basis prohibited by law.

The salary range for this position is $25-28/hour. The base salary represents Arcadis' hiring range for this position. Actual salaries will vary and will be based on various factors, such as location, skills, experience, and qualification for the role.