Director, Data Science & Engineering, Finance

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead a dynamic, high-performing team consisting of a data scientist and a data engineer dedicated to supporting the Finance department.

• Oversee, mentor, and nurture team members by setting clear expectations, creating development plans, and promoting delegation and ownership.

• Define the team's strategy and priorities across various strategic initiatives, ongoing operations, model maintenance, knowledge management, and addressing technical debt.

• Provide technical direction in the realms of data science and data engineering, covering problem framing, modeling, data architecture, pipeline development, testing, monitoring, documentation, and ensuring production readiness.

• Identify and set standards for artificial intelligence, machine learning, automation, advanced analytics, experimentation, evaluation, interpretability, human oversight, privacy, and monitoring procedures.

• Enhance the quality, lineage, observability, documentation, governance, and reliability of financial data.

• Ensure that models and analyses effectively support financial planning, forecasting, understanding drivers, and facilitating decision-making processes.

• Create operational frameworks for project intake, prioritization, roadmaps, reviews, incident management, documentation, knowledge sharing, and communication with stakeholders.

• Articulate the implications, recommendations, risks, and trade-offs of data, models, and engineering to both technical and non-technical audiences, including Finance and executive leadership.

• Collaborate with stakeholders across Finance, Engineering, Data, Product, software engineering, and executive levels.

• Automate routine tasks, enhance service levels, and amplify the strategic contributions of the team.

⛳️ Requirements

• A Bachelor’s degree or higher in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field, or equivalent practical experience.

• Extensive experience applying data science, machine learning, analytics, data engineering, or a combination of these fields to solve business challenges.

• Proven experience in managing and developing technical professionals, ideally including both data scientists and data engineers or similarly aligned roles.

• A strong foundational understanding in either data science or data engineering, with a proven ability to effectively collaborate across the other area.

• Demonstrated experience leading a portfolio of projects from problem identification through to delivery, adoption, assessment, and ongoing management.

• Familiarity with data quality, data pipelines, analytical datasets, model development or maintenance, experimentation or evaluation, and production or operational support.

• Proven ability to leverage data and technology to impact business decisions positively and deliver measurable results.

• Excellent communication and stakeholder management skills, with the capacity to convey technical concepts, uncertainties, and trade-offs to Finance and executive audiences.

• A demonstrated growth mindset: actively seeking feedback, acquiring new technologies and knowledge domains, adapting to evolving conditions, and fostering an environment for team growth.

• Capability to operate with a high level of autonomy and ownership in a fast-paced, ambiguous environment.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and flexible work hours.

• Opportunities for professional development and continuous learning.

• Collaborative and inclusive work culture.