Data Science Intern
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Job Description
About the Company
WayUp is the leading platform dedicated to connecting early-career candidates with premier internship and entry-level job opportunities. They collaborate with a diverse range of organizations, from startups to Fortune 500 companies and mission-driven entities, to facilitate the discovery and hiring of top talent. In this particular context, WayUp is partnering with companies (implied as “WayUp” in the initial sentence, but the context makes it clear WayUp is the platform/recruiter) to source candidates for their client companies.
About the Job: Data Science Intern (Talent Pool)
This is not a live job listing but rather a submission of interest to a talent pool managed by WayUp. By submitting your profile, WayUp will notify you when relevant Data Science Intern opportunities become available with their partner companies. If your background aligns with a client’s specific needs, you may be contacted directly for the next steps in their hiring process.
About the Roles:
As a Data Science Intern, you will gain comprehensive, hands-on experience by converting raw data into actionable and meaningful insights. Interns will work on real-world projects alongside seasoned data scientists and analysts, leveraging data to inform critical business decisions, enhance products, and drive strategic initiatives. This internship provides a front-row seat to the entire data lifecycle, encompassing everything from data wrangling and modeling to effectively communicating insights to various stakeholders.
What You Might Work On:
• Cleaning, transforming, and analyzing large datasets using popular programming languages like Python, SQL, or R.
• Building predictive models and conducting in-depth statistical analyses.
• Visualizing data and effectively communicating insights to diverse cross-functional teams.
• Supporting and contributing to A/B testing, experiment design, or KPI (Key Performance Indicator) analysis.
• Collaborating with engineering, product, or business teams to solve real-world problems using data-driven approaches.
Who This is For (Qualifications):
• Students graduating in late 2025, 2026, or 2027 pursuing a degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related quantitative field.
• Demonstrated experience with one or more programming languages commonly used in data science, such as Python, R, or SQL.
• Familiarity with essential data manipulation libraries (e.g., pandas, dplyr) and fundamental statistical concepts.
• Possession of strong problem-solving and communication skills.
• A high degree of curiosity and the ability to work effectively both independently and within small, collaborative teams.
• Bonus qualifications include exposure to machine learning libraries (e.g., scikit-learn, XGBoost) or proficiency with data visualization tools (e.g., Tableau, Power BI, matplotlib).
Technologies You May Be Exposed To:
• Programming & Analysis: Python, R, SQL, Jupyter Notebooks
• Data Tools & Libraries: pandas, NumPy, scikit-learn, TensorFlow, Spark
• Data Visualization: Tableau, Power BI, matplotlib, seaborn
• Cloud Platforms: AWS (e.g., S3, Redshift), Google Cloud (e.g., BigQuery), Azure
• Data Engineering & Pipelines: Airflow, dbt, Snowflake, Kafka
