P
2 months ago
Job Summary
Our data team plays a pivotal role in driving analytics into our go-to-market and R&D investments, while also embedding powerful reporting into our customer-facing products. This enables gym owners to make decisions that optimize their business performance, from predicting membership churn to identifying upsell opportunities. Our data scientists and data engineers collaborate closely with our executive team and customers to integrate analytics into the core of our strategic decision-making process.
- Minimum Qualification : Degree
- Experience Level : Mid level
- Experience Length : 3 years
Job Description/Requirements
What you will be doing:
- Collaborate with business stakeholders, product managers, and engineers to identify opportunities for leveraging data to drive business value.
- Design and implement advanced analytics models to solve complex business problems and improve decision-making.
- Conduct exploratory data analysis to uncover insights, patterns, and trends, and communicate findings to stakeholders through clear visualizations and reports.
- Contribute to building a robust data infrastructure by working closely with data engineers to define core data models, ensure data quality, and create a single, unified customer view.
- Leverage data from multiple sources, including third-party vendor tools, to build comprehensive analytics solutions that drive business growth.
- Continuously monitor and optimize the performance of deployed models, ensuring their reliability, accuracy, and business impact.
What you’ll bring to the table:
- A minimum of 3 years of experience in data science or a related field, with a strong foundation in statistics, machine learning, and data mining techniques.
- Proficiency in statistical programming languages such as Python or R, and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with SQL and working with large datasets, data warehouses, and data lakes.
- Excellent problem-solving skills and the ability to design and implement efficient, scalable, and pragmatic data science solutions.
- Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Optional: Advanced degree in a quantitative field (e.g., Computer Science, Statistics, Physics) and experience with deep learning, natural language processing, or computer vision techniques.
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