How you will spend your time at Tovala
- Develop robust, scalable demand models using Python and advanced statistical techniques.
- Design and implement causal models to inform strategic and investment decisions.
- Leverage simulation techniques to assess business scenarios and improve decision quality.
- Build intuitive user interfaces and visualizations to make complex insights accessible.
- Lead analytics projects from ideation to deployment, ensuring models are tested, validated, and production-ready.
- Collaborate with analysts and business stakeholders to combine critical domain knowledge with advanced analytics methodologies to design actionable solutions to business problems.
- Optimize and refine models for computational efficiency and scalability, particularly for large datasets.
- Partner closely with data engineers to deploy models and build out a code library.
- Build out tables and definitions within the ETL to support business initiatives.
- Contribute to the overall data strategy by identifying new data sources, tools, and methodologies to enhance analytical capabilities.
- Manage multiple projects simultaneously, balancing short-term needs with long-term strategic initiatives.
- Regularly conduct code reviews and technical deep dives with peers to ensure high-quality model deployment and adherence to best practices.
- Participate in data governance and help set the framework for good data practices at Tovala.
About you
- You have an advanced degree (Master’s or PhD) or equivalent experience in a technical field (e.g., Statistics, Data Science, Mathematics, Computer Science, or related discipline).
- You have 5+ years of experience in a data science role, with a proven track record of solving complex problems using machine learning and statistical models.
- You have strong programming skills in Python, including experience with advanced machine learning libraries such as TensorFlow, Keras, PyMC, or equivalent.
- You are proficient in SQL and have experience working in a data warehouse environment (preferably Snowflake)
- You understand causal inference and have experience with frameworks like DoWhy or causal ML packages.
- You have experience with time series analysis and applying Bayesian methods.
- You are familiar with simulation techniques (e.g., MCMC, agent-based modeling) and their business applications.
- You have experience collaborating with engineering teams to deploy models into production and are proficient in version control (e.g., Git).
- You have strong communication skills and are able topresent complex findings to technical and non-technical audiences in a clear and actionable way; experience with BI tools is a plus.
- You are a collaborative team player who is comfortable both giving and receiving feedback.
- You are a proactive learner with a growth mindset, constantly seeking to enhance your knowledge and skills.
- You are comfortable working independently with minimal oversight, while driving technical initiatives forward.
- You have strong project management skills with the ability to prioritize and balance multiple complex projects.
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