Embrace is looking for a Data Science Intern to join our data science team. This hands-on, high-impact internship focuses on uncovering patterns and insights within billions of mobile and web events collected for our customers' applications. You'll apply modern data science and machine learning to large-scale, real-world observability and user session data.
What You'll Do
- Explore, analyze, and visualize large datasets from mobile and web observability and user session data.
- Develop statistical measures and applied models to identify meaningful classifications, trends, anomalies, or predictive signals in event data.
- Partner with Embrace staff from product and data science to prioritize research projects and translate research insights into potential product features.
- Present findings to technical and non-technical audiences.
- Contribute to documentation, reproducible notebooks, and internal demos.
What We're Looking For
- Currently enrolled in a Master’s program in Data Science, Computer Science, or a related quantitative field.
- Proficient in Python and familiar with key data science frameworks (e.g., Pandas/Polars, NumPy, scikit-learn, and data visualization libraries like matplotlib or seaborn).
- Foundational understanding of machine learning concepts (supervised, unsupervised, feature engineering, evaluation metrics).
- Ability to query and manipulate large datasets using SQL or PySpark.
- Strong analytical and problem-solving skills with attention to detail.
- Excellent written and verbal communication skills.
- Curiosity and enthusiasm for working with large-scale, real-world data.
Nice to Have
- Experience working with time-series or event-based data.
- Experience with data visualization tools (e.g., Plotly, Dash, Streamlit, or similar).
- Familiarity with non-parametric statistics on event-based data.
- Familiarity with deep learning frameworks like PyTorch or TensorFlow and judgement on when to use them.
- Familiarity with cloud data ecosystems (e.g., ClickHouse, Snowflake, BigQuery, AWS, or GCP).
- Contributions to open-source projects or independent research projects.
- Excitement about learning from experienced engineers and seeing your work influence product direction.
Technical Stack
- Python, Pandas/Polars, NumPy, scikit-learn, matplotlib/seaborn
- SQL, PySpark
- Plotly/Dash/Streamlit, PyTorch/TensorFlow
- ClickHouse/Snowflake/BigQuery/AWS/GCP
Team & Environment
You will work closely with product and engineering teams. Our culture values continuous improvement as individuals, team members, and as a company.
Work Mode
This is a remote position open to candidates in the United States.
