Data Science Intern
- Role
- Data Science
- Experience
- Entry level
- Employment
- Part-time
Open to IN only. Set where you work from to check your eligibility.
No BS summary
This is an open collaboration program designed for aspiring data scientists to gain hands-on, real-world experience. Work on actual business challenges, build your machine learning portfolio, and learn by doing alongside our team.
Core skills
Required skills
Optional skills
Role OverviewAt GenesectAi, we're doing things differently. This isn't a traditional job or a standard internship—it’s an open collaboration program designed for aspiring data scientists to gain hands-on, real-world experience. If you are self-taught, a student, or transitioning careers, this is a space for you to work on actual business challenges, build your machine learning portfolio, and learn by doing alongside our team.ResponsibilitiesProcess & Prep Data: Clean, preprocess, and engineer features from messy, real-world datasets.Explore & Analyze: Conduct Exploratory Data Analysis (EDA) to uncover hidden patterns, trends, and correlations.Train & Test Models: Build, tune, and evaluate foundational machine learning algorithms (e.g., regression, classification, clustering).Communicate Findings: Translate complex statistical outputs and model results into clear, actionable business insights.RequirementsPassionate about machine learning and eager to learn (no specific degree required).Solid grasp of Python or R, including standard data libraries.Familiar with foundational statistics, probability, and basic predictive modeling.Curious, driven, and comfortable asking questions.Nice to HaveExperience with Deep Learning, NLP, or SQL.Experience building end-to-end projects.SkillsPythonPandasScikit-learnSQLMachine LearningBenefitsRemote & Flexible: Contribute from anywhere, on a schedule that works for you.Real Portfolio Projects: Leave with end-to-end data science projects to show future employers.Direct Mentorship: Get honest feedback and guidance from our core team.Proof of Impact: A certificate of completion and a strong letter of recommendation.
What you'll do
- Clean, preprocess, and engineer features from messy, real-world datasets.
- Conduct Exploratory Data Analysis (EDA) to uncover hidden patterns, trends, and correlations.
- Build, tune, and evaluate foundational machine learning algorithms (e.g., regression, classification, clustering).
- Translate complex statistical outputs and model results into clear, actionable business insights.
What they require
- Passionate about machine learning and eager to learn (no specific degree required).
- Solid grasp of Python or R, including standard data libraries.
- Familiar with foundational statistics, probability, and basic predictive modeling.
- Curious, driven, and comfortable asking questions.
Benefits
- Contribute from anywhere, on a schedule that works for you.
- Leave with end-to-end data science projects to show future employers.
- Get honest feedback and guidance from our core team.
- A certificate of completion and a strong letter of recommendation.