Principal, Data Scientist (Finance)

Datasite and its associated businesses are the global center for facilitating economic value creation for companies across the globe. From data rooms to AI deal sourcing

and more. Here you’ll find the finest technological pioneers: Datasite, Blueflame AI, Firmex, Grata, and Sherpany. They all, collectively, define the future for business growth.

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Job Description:

As a Principal Data Scientist, you will be the technical lead and primary "engine" of our data science initiatives. Reporting to the Director of Data Science, you are a high-level individual contributor responsible for solving our most complex, abstract business problems through advanced mathematical modeling. You will lead the end-to-end development of "Data Intelligence Products" - from high-dimensional forecasting and financial risk engines to ML-driven revenue optimization. While this is an IC role, you will set technical standard for the department, acting as a mentor to junior analysts and an architect for our predictive ecosystem.

Responsibilities

1. Advanced Technical Execution (The Engine)

• Elite Predictive Modeling: Lead the research, design, and deployment of sophisticated models for time-series revenue forecasting, unit economics, and profitability.
• Risk & Uncertainty Quantification: Develop advanced statistical tools to predict financial risk and operational volatility, providing the business with probabilistic guardrails.
• Algorithmic Innovation: Move beyond standard libraries to build custom ML solutions that address the specific nuances of our finance and project data.
• Experimental Design: Architect rigorous A/B and multivariate testing frameworks to measure the causal impact of business decisions and product iterations.

2. Technical Architecture & Productization (The Bridge)

• Model Orchestration: Partner with the Data Engineering team to design the "last mile" of ML deployment—ensuring your models run reliably within our Snowflake/dbt environment.
• Seamless Integration: Ensure model outputs are elegantly integrated into Power BI semantic models, turning complex statistical distributions into actionable business signals.
• Code Excellence: Set the bar for the Data Science "Playbook," establishing rigorous standards for reproducible research, version control, and model validation.

3. Strategic & Technical Leadership (The Growth)

• Discovery & R&D: Proactively identify opportunities for ML/AI to drive ROI, staying ahead of industry trends in LLMs, deep learning, and predictive analytics.
• Abstract Problem Solving: Take high-level business queries from the Director or C-suite and translate them into mathematically sound, executable project plans.
• The Intelligence Stack: Expert-level mastery of Python and SQL. Extensive experience deploying production-grade models within a cloud environment (Snowflake preferred).

The Ideal Candidate Profile

Technical Mastery

• The ML Toolbelt: Deep expertise in the Python Data Science stack (e.g., scikit-learn, XGBoost, LightGBM) and deep learning frameworks (e.g., PyTorch or TensorFlow).

• Predictive Expertise: Deep experience in time-series forecasting, supervised learning, and causal inference. Time-Series & Forecasting: Mastery of libraries dedicated to financial and demand forecasting, such as Prophet, statsmodels, or sktime.
• MLOps & Deployment: Experience with model lifecycle management tools (e.g., MLflow, Weights & Biases) and deploying models via containers (Docker/Kubernetes) or as serverless functions.
• Statistical Logic: You don't just run models; you understand the "why" behind the math and can defend your methodology to technical and non-technical audiences.
• Mathematical Depth: Deep expertise in supervised/unsupervised learning, Bayesian statistics, time-series analysis, and causal inference.
• Generative AI & LLMs: Working knowledge of integrating LLMs (via LangChain, OpenAI API, or Hugging Face) into business workflows for unstructured data analysis.
• The Modern Data Stack: Proficiency in using Snowflake as a feature store and dbt for feature engineering.

Business & Leadership Skills

• Finance Acumen: You understand the levers of a P&L and how predictive modeling impacts revenue and margin.
• Communication: Exceptional ability to simplify complex "black box" concepts for executive stakeholders.

Qualifications

• 8–10+ years of experience in Data Science, with a track record of delivering high-impact predictive models in a corporate or production environment.
• Proven IC Leadership: Experience as a staff or principal-level contributor who has successfully led large-scale technical projects from concept to deployment.
• Modern Stack Experience: Deep familiarity with the Snowflake + dbt + Power BI ecosystem is a significant advantage.
• Proven track record of building and deploying predictive models using Python and SQL that achieved high business adoption.
• Toolkit Expertise: Hands-on experience with ML orchestration tools and automated testing for model performance (e.g., monitoring for Data Drift and Model Decay).
• Cloud Infrastructure: Experience with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker, or Databricks) and how they integrate with data warehouses like Snowflake.
• Advanced Education: PhD or Master’s degree in a highly quantitative discipline (e.g., Physics, Mathematics, Statistics, Computer Science, or Economics).

The base salary range represents the estimated low and high end for this position based on a good faith assessment of the role and market data at the time of posting. Consistent with applicable law, each candidate’s compensation offer may vary and will be determined based on but not limited to, your geographic region, skills, qualifications, and experience along with the requirements of the position. This position may be eligible for bonuses, commissions, or overtime if applicable. Benefits include health insurance (medical, dental, vision), a retirement savings plan, paid time off, and other employee benefits. Specific details will be provided during the interview process. Datasite reserves the right to modify this pay range at any time.

Our company is committed to fostering a diverse and inclusive workforce where all individuals are respected and valued. We are an equal opportunity employer and make all employment decisions without regard to race, color, religion, sex, gender identity, sexual orientation, age, national origin, disability, protected veteran status, or any other protected characteristic. We encourage applications from candidates of all backgrounds and are dedicated to building teams that reflect the diversity of our communities.