Data Scientist - Analytical/Python

At DevSavant, we are a trusted technology partner specializing in Software Development, Data Engineering, AI/Machine Learning, Cloud Solutions, Automation Testing, and UI/UX Design. We deliver innovative, high-quality solutions with a focus on excellence and results. Our people are at the heart of everything we do, fostering a culture of growth and well-being. Join us and thrive in a supportive, success-driven environment.

Our client is a data and analytics startup that aims to expand knowledge of subscriber behavior so brands can entertain, inspire, and empower the world. They provide industry and competitive benchmarks across key metrics so the customers can know ‘what good looks like’, market intelligence so they can learn how to build a best-in-class business, and insights to inform their strategic decision-making. They are quickly becoming the market standard for subscription analytics. They have defined product/market fit, secured household names as clients, and are in ‘hyper-growth’ mode!

We're looking for a talented Data Scientist who is great at both analyzing data and writing strong Python code. You'll play a key role in finding important insights in large datasets, creating engaging data charts, and also helping to build and improve the core Python tools and libraries. The data science team uses it every day. You'll work closely with experienced data scientists, helping them understand complex data, share findings clearly, and make the analytical codebase even better. If you love digging into data, telling stories with it, and writing excellent Python code to solve analytical problems, this job is for you!

You will report to the Senior Manager, Data Science. We are looking for candidates who can work during US business hours.

What You’ll Do

• Explore diverse datasets to find trends, patterns, and useful insights.

• Create and maintain clear data charts, dashboards, and reports using Python (like Plotly, Seaborn) and BI tools (like Looker).

• Contribute to the design, development, and testing of Python modules and utilities within our core data science library.

• Write reusable, well-documented Python code (including classes and functions) to support analytical tasks and machine learning models.

• Work on Labs projects, using your analytical and Python skills on new data and experiments.

• Prepare, clean, and check data to support data science models and analytical projects.

• Clearly write down your analytical methods, your Python code contributions, and how your charts work.

• Explain complex data and analytical results in a simple way to both technical and non-technical people.

Who You Are

• You have 1-3 years of work experience in a data-focused job, with a strong emphasis on data analysis, finding insights, making charts, and developing Python code for these tasks.

• You have strong Python programming skills. You can write clear, well-structured, and testable Python code, including custom classes and functions. You're comfortable contributing to a shared codebase or internal libraries.

• You are skilled with Python data analysis tools like Pandas, NumPy, and chart-making tools (e.g., Plotly, Seaborn, Matplotlib).

• You have strong SQL skills for getting, changing, and exploring complex data.

• You are good at turning data into interesting stories and effective charts.

• You are comfortable using Git to manage your code and projects.

• You have some experience with cloud data systems (GCP and BigQuery are a big plus) for accessing data and running analyses.

• You understand basic machine learning ideas and can help explain what model results mean.

• You are an excellent problem-solver for both analytical questions and Python coding challenges, with a good eye for detail.

• You communicate clearly in English, especially when presenting data-based findings and technical ideas. Advanced English proficiency (B2-C1)

• You are excited to learn, happy to work as part of a team, and can take guidance from senior team members.

Bonus:

• Experience in or passion for the Subscription Economy, especially in media and entertainment.

• Experience with BI tools like Looker or Tableau.

• Familiar with designing experiments (e.g., A/B testing).

Tech Stack (Required Proficiency)

• Languages: Python, SQL

• Cloud Platform: Google Cloud (Storage, Dataproc, BigQuerY)

• Version Control: Git

• Data Analysis Libraries: Pandas, NumPy, SciPy

• Machine Learning: scikit-learn, TensorFlow, or PyTorch

• Data Visualization: Looker, Plotly, Google Data Studio

• AI Tools: Claude, Gemini, OpenAI offerings