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Job Description:

As the Director of Data Science, you will be the founding architect of our data science function and you will lead the evolution of our intelligence layer. You are responsible for transforming complex, abstract business problems into rigorous predictive models and experimentation frameworks. You will lead 1 or 2 Data Scientists to build "Data Intelligence Products" example: automated forecasting tools, risk prediction engines, and ML-driven initiatives that directly impact revenue and profitability. You are part Hands-on Scientist and part Strategic Builder, bridging the gap between abstract problem solving and concrete business outcomes.

Responsibilities

1. Intelligence & Model Development (The Engine)

• High-Impact Modeling: Directly oversee and contribute to the development of predictive models for revenue forecasting, profitability, and demand planning.
• Risk Prediction Tools: Architect and deploy tools for predictive financial risk assessment, helping the business identify and mitigate volatility before it occurs.
• ML/AI Roadmap: Define the vision for how AI/ML will be integrated into our modern data stack (Snowflake/dbt/Power BI) to automate complex decision-making.
• Experimentation Rigor: Establish the framework for A/B testing and statistical experimentation to validate business strategies and product changes.

2. Strategic Leadership & Ambiguity Management (The Bridge)

• Abstract Problem Solving: Serve as the primary partner to the C-suite, translating vague business challenges into structured data science projects with clear ROI.
• Stakeholder Management: Work cross-functionally (Finance, Marketing, Ops) to ensure that predictive insights are not just "interesting," but are integrated into the operational workflow.
• Data Productization: Partner with Data Engineering to ensure models are "production-ready," moving them from local scripts to automated, reliable outputs in Power BI.

3. Department Building & Talent Pipeline (The Growth)

• Team Scaling: 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.
• Talent Pipeline: 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.
• Standard Setting: Establish the "Data Science Playbook"—defining our standards for code quality, model validation, and documentation.

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.

Business & Leadership Skills

• Entrepreneurial Spirit: You are excited by the prospect of building a department from the ground up, from selecting tools to hiring the team.
• 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

• 10+ years of experience in Data Science or Advanced Analytics, with 3+ years in a leadership capacity.
• Proven track record of building and deploying predictive models (Revenue, Risk, or Forecasting) that achieved high business adoption.
• 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.

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.

$167,000.00 - $300,400.00

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.