Senior Data Scientist - Model Strategy Management

The Advanced Insights and Modeling (AIM) team is a high-impact, business-savvy group of builders—comprising machine learning engineers, data scientists, data engineers, and business strategists—who blend cutting-edge machine learning with deep product and financial insight. Known for high standards, rapid execution, and full-stack model ownership, they deliver scalable, high-value solutions across domains. AIM thrives on curiosity, bold thinking, and collaboration, fostering a magnetic, non-corporate culture. Trusted across the company, they are a go-to partner for insight, speed, and transformative business impact.

The AIM team plays a pivotal role in developing and scaling AI-driven predictive metrics that inform strategic investment decisions and drive operational excellence across the company. These metrics such as revenue inflow and outflow, active customer counts, customer lifetime value, and sales prospect value are foundational to planning and execution across Finance, Marketing, Sales, Product, and Risk, enabling high-confidence, data-informed decisions at scale.

We are seeking a Senior Data Scientist to support our ML Business Modeling team within the Advanced Insights & Modeling group. This role requires a strong sense of business strategy, Economic insight, data science expertise, and Machine Learning modeling experience. A successful candidate will lead the development of business models, manage project timelines, and execute post-development model performance testing framework. As a Data Scientist, you will be the liaison between Engineers and Business teams, translating business requirements into modelable exercises.

You Will

1. Participate in the development and implementation of advanced predictive models to support strategic business decisions.
2. Manage project timelines and deliverables, ensuring the timely completion of data science initiatives.
3. Prioritize model development efforts based on business impact and strategic objectives.
4. Collaborate with machine learning engineering teams to build and maintain robust end-to-end data pipelines.
5. Conduct early-stage analysis to inform model development, leveraging business intuition to suggest key drivers and features.
6. Own parallel modeling to ensure alignment with business expectations and reporting.
7. Interface with business stakeholders to gather requirements and ensure models meet business needs.
8. Explore improvements to business analytics using LLMs and other productivity tools.

You Have

1. Bachelor’s with 5+ or Master’s with 3+ years of experience in finance, economic analysis, data science, or a related field, with a focus on applying analytic tools to business problems.
2. Expertise in forecasting, predictive modeling, and value estimation, including statistical and ML-based methods.
3. Advanced proficiency in Python, and experience with libraries such as scikit-learn, XGBoost, LightGBM, and pandas/numpy.
4. Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
5. Demonstrated ability to work collaboratively across teams and functions.

Technologies We Use and Teach

1. SQL
2. Python (Streamlit, Sklearn, Prefect)
3. GitHub
4. Databricks

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Zone A:

$163,600—$245,400 USD

Zone B:

$155,400—$233,200 USD

Zone C:

$147,300—$220,900 USD

Zone D:

$139,000—$208,600 USD