Note: The job is a remote job and is open to candidates in USA. Inmar Intelligence is seeking a part-time Data Science Intern to support its MarTech Data Science team. The role contributes to data pipelines, machine learning models, and analytics solutions for the company’s media and incentives businesses.
Responsibilities
- Assist in developing and maintaining reusable components for data transformation, feature extraction, and model deployment using cloud technologies, primarily Google Cloud Platform
- Support the development and deployment of machine learning models and analytics pipelines
- Collaborate with internal teams to develop data-driven solutions for business and product needs
- Assist with ad-hoc analyses and identify opportunities to improve or standardize recurring analytical processes
- Utilize AI tools to support coding, analysis, and problem-solving while following appropriate validation and review practices
- Contribute to ongoing team projects and technical documentation as needed
Skills
- Currently pursuing a Bachelor's or Master's degree in Data Science, Statistics, Data Engineering, Computer Science, or a related quantitative field
- Experience with SQL and cloud-based data platforms, preferably Google Cloud Platform
- Experience with AWS, Azure, or Spark is also relevant
- Experience with statistical programming languages and machine learning frameworks, including Python, R, SAS, TensorFlow, or PyTorch
- Familiarity with AI-assisted coding and problem-solving tools, including appropriate validation and review practices
- Strong analytical, organizational, communication, and problem-solving skills
- Ability to work independently and collaboratively with cross-functional teams
- Candidates must have authorization to work in the U.S. without the need for employer sponsorship now or in the future
- Preferably Google Cloud Platform
Benefits
- Opportunity to apply academic knowledge in a professional setting while gaining experience with data science, machine learning, and cloud-based technologies.
- Work alongside experienced professionals and contribute to ongoing projects.
- Develop technical and professional skills through practical experience and collaboration.
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