Eda Data Science Senior Manager

Job Requisition ID #
- 23WD73736

Position Overview

The Enterprise Data and Analytics (EDA) organization is on a mission to empower accurate decisions using certified customer data and insights product across all Autodesk customer-facing teams. The data science team is at the heart of developing and delivering Decision Intelligence solutions for both strategic and operational customer engagement teams. Our team applies descriptive, predictive, prescriptive, experimental, and causal methodologies to facilitate and orchestrate decisioning for Autodesk's customer experience teams. You will work with program management, analytic engineering, and federated analytics teams to deliver unified decision experiences. You will work on multiple problem areas in customer success, marketing, and sales such as retention/churn prediction, upsell/cross-sell/growth potential, customer segmentation, benchmarking, propensity scoring, attribution modeling, what-if scenarios and next-best action.

We are looking for a dynamic Data Science Sr. Manager to join our leadership team. You will lead our diverse data science team and drive our data science Decision Intelligence initiatives.You are excited about the challenges that come with growth, and passionate about connecting people together through a positive and inclusive culture. You have a combination of technical expertise, people management skills, operating with strategic vision for translating business objectives into appropriate statistical problems that facilitate business decision experiences that promote evidence-based culture.

You will report into the Sr. Director Enterprise and Analytics. Depending on you location you can work remote or hybrid.

**Responsibilities**:

- You will own the operational and delivery aspects of the data science organization. We expect leadership and close collaboration and alignment with leadership strategic initiatives that foster Decision Intelligence across Autodesk
- You are a critical thinker, strategic thought partner, who exhibits extreme ownership who thrives on execution
- Work with your team, executives, and the broader data organization to deliver strategic insights and build data products to lead operational efficiency and help Autodesk meet its goals
- Lead the end-to-end development and deployment of data science projects related to retention, churn, license compliance, lead generation, segmentation, and attribution, from problem formulation to model implementation and evaluation
- Manage a portfolio of projects in collaboration with EDA program management, ensuring delivery and alignment with business objectives for marketing, sales, and customer success
- Collaborate with cross-functional teams, including data engineers, product managers, and business stakeholders, to define project requirements and deliverables
- Provide technical guidance and mentorship to the data science team, encouraging a culture of continuous learning and innovation
- Conduct regular performance evaluations, provide feedback, and identify opportunities for skills development and growth

Minimum Qualifications
- M.S.in a quantitative field (mathematics, statistics, or similar STEM field)
- 8+ years of experience in data science, machine learning, or a related field
- 3+ years of experience managing teams
- Proficiency in programming languages such as Python or R, and experience with data analysis using SQL
- Experience with statistical modeling, machine learning algorithms, experimentation, and data visualization techniques
- The ability to present complex concepts to all levels of stakeholders
- Experience building relationships to influence product partners with data, analysis, and leading cross-functional projects that depend on the contributions of others in multiple disciplines
- In-depth knowledge of data manipulation, data integration, and database management
- The ability to align data strategies with business objectives
- The ability to identify the right business problems to solve
- The ability to derive actionable insights from complex data

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