Datasite is looking to establish and lead its data science function, transforming complex business problems into rigorous predictive models and experimentation frameworks to drive revenue and profitability.
Requirements
- Deep expertise in the Python Data Science stack (e.g., scikit-learn, XGBoost, LightGBM) and deep learning frameworks (e.g., PyTorch or TensorFlow).
- Deep experience in time-series forecasting, supervised learning, and causal inference.
- Mastery of libraries dedicated to financial and demand forecasting, such as Prophet, statsmodels, or sktime.
- Experience with model lifecycle management tools (e.g., MLflow, Weights & Biases) and deploying models via containers (Docker/Kubernetes) or as serverless functions.
- Deep expertise in supervised/unsupervised learning, Bayesian statistics, time-series analysis, and causal inference.
- Working knowledge of integrating LLMs (via LangChain, OpenAI API, or Hugging Face) into business workflows for unstructured data analysis.
- Proficiency in using Snowflake as a feature store and dbt for feature engineering.
Responsibilities
- Directly oversee and contribute to the development of predictive models for revenue forecasting, profitability, and demand planning.
- Architect and deploy tools for predictive financial risk assessment, helping the business identify and mitigate volatility before it occurs.
- Define the vision for how AI/ML will be integrated into our modern data stack (Snowflake/dbt/Power BI) to automate complex decision-making.
- Establish the framework for A/B testing and statistical experimentation to validate business strategies and product changes.
- Partner with Data Engineering to ensure models are "production-ready," moving them from local scripts to automated, reliable outputs in Power BI.
- Act as a "Player-Coach" to the current Data Science team while identifying the specific skill gaps (e.g., NLP, Deep Learning, MLOps) needed for future hires.
- Establish the "Data Science Playbook"—defining our standards for code quality, model validation, and documentation.
Other
- Serve as the primary partner to the C-suite, translating vague business challenges into structured data science projects with clear ROI.
- Work cross-functionally (Finance, Marketing, Ops) to ensure that predictive insights are not just "interesting," but are integrated into the operational workflow.
- Proactively build a network and recruitment strategy for future Data Analytics and Data Science roles to ensure rapid scaling as the function proves its value.
- You are excited by the prospect of building a department from the ground up, from selecting tools to hiring the team.
- You understand the levers of a P&L and how predictive modeling impacts revenue and margin.
