Senior Principal Data Scientist, Advanced Forecasting
Edwards Lifesciences
Senior Principal Data Scientist, Advanced Forecasting
Job Description
Imagine how your ideas and expertise can change a patient’s life. Patients are at the heart of what we do at Edwards Lifesciences. Our Finance teams work hard to optimize our current and long-term success and enable our ongoing strategy of innovation, leadership, and focus. As part of the team, whether providing analysis, forecasting, or reporting financial information, your application of accurate financial business practices will play a fundamental role in how we impact the quality of life for patients all over the world.This role sits at the intersection of Corporate Finance (FP&A) and advanced analytics / data science. The Senior Manager will serve as a bridge to translating data into actionable financial insights. This role will build and operationalize statistical forecasting and scenario models to improve planning accuracy and decision quality — partnering closely with Finance leaders and enabling this capability in our planning platform (Anaplan). The role will help stand up an Advanced Forecasting Center of Excellence across Finance, setting standards for advanced model governance, validation, and repeatable planning playbooks.On-site in Irvine How you’ll make an impact: Build and maintain data-driven forecasting models (time-series, AI/ML, causal/driver-based, Monte Carlo / probabilistic scenarios) for key financial and operational outcomes (revenue, margin, opex, cash flow, etc.)Act as a strategic partner to the Anaplan planning program: define requirements for data-based forecasting and ensure outputs integrate cleanly into planning workflows.Build “last mile” adoption: templates, dashboards, documentation, and stakeholder training so teams can consistently use the statistical outputs in planning and reviews.Communicate complex findings clearly: concise executive narratives, visuals, and recommendations grounded in data.Establish model testing/validation routines (back-testing, error metrics, drift monitoring) and create clear documentation for assumptions, limitations, and controls.Partner with FP&A to marry insights from management forecasts with data-driven insights from the statistical forecasts.Design scenario and sensitivity frameworks that quantify tradeoffs, risks, and uncertainty translating outputs into actionable insights for Finance and business leaders.Stand up an Advanced Forecasting Center of Excellence: modeling standards, reusable code/modules, data definitions, governance, and prioritization intake.Collaborate with Data/IT to improve pipelines, data quality/governance, and automation; ensure models are scalable, maintainable, and auditable.Other incidental dutiesWhat you'll need (Required):Bachelor's Degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, BiostatisticsA minimum of ten years of experience including either industry or industry/education or equivalent work experience (OR eight years with a Masters OR four years with a PH.D)What else we look for (Preferred): Strong hands-on capability in Python or R, plus SQL; comfortable with large datasets and model lifecycle basics.Excellent communication and interpersonal skills, with the ability to engage stakeholders at all levels.Proven expertise in statistical techniques (e.g. distributions, statistical testing, regression, etc.)Working knowledge in related tools and applications (e.g., Oracle, JDE, Concur, Salesforce.com) preferredStrict attention to detailExtensive knowledge and understanding of principles, theories, and concepts relevant to Artificial Intelligence (AI) and/or Machine Learning model development, and/or Control Systems.Experience with planning platforms (e.g., Anaplan) and driver-based planning / forecasting frameworks.Familiarity with cloud/data platforms (e.g., Databricks/Azure/AWS equivalents) and modern analytics workflows.Experience setting standards, leading cross-functional work, and building repeatable playbooks.Aligning our overall business objectives with performance, we offer competitive salaries, performance-based incentives, and a wide variety of benefits programs to address the diverse individual needs of our employees and their families.For California (CA), the base pay range for this position is $145,000 to $205,000 (highly experienced).The pay for the successful candidate will depend on various factors (e.g., qualifications, education, prior experience). Applications will be accepted while this position is posted on our Careers website. Edwards is an Equal Opportunity/Affirmative Action employer including protected Veterans and individuals with disabilities.
Locations
- USA - California – Irvine
Salary
145,000 - 205,000 USD / yearly
Skills Required
- statistical techniquesintermediate
- planning platformsintermediate
- cloud/data platformsintermediate
Required Qualifications
- Bachelor's Degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, Biostatistics (degree in finance)
- A minimum of ten years of experience including either industry or industry/education or equivalent work experience (OR eight years with a Masters OR four years with a PH.D) (experience)
- Bachelor's Degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, Biostatistics (degree in finance)
- A minimum of ten years of experience including either industry or industry/education or equivalent work experience (OR eight years with a Masters OR four years with a PH.D) (experience)
Preferred Qualifications
- Strong hands-on capability in Python or R, plus SQL; comfortable with large datasets and model lifecycle basics. (experience)
- Excellent communication and interpersonal skills, with the ability to engage stakeholders at all levels. (experience)
- Proven expertise in statistical techniques (e.g. distributions, statistical testing, regression, etc.) (experience)
- Working knowledge in related tools and applications (e.g., Oracle, JDE, Concur, Salesforce.com) preferred (experience)
- Strict attention to detail (experience)
- Extensive knowledge and understanding of principles, theories, and concepts relevant to Artificial Intelligence (AI) and/or Machine Learning model development, and/or Control Systems. (experience)
- Experience with planning platforms (e.g., Anaplan) and driver-based planning / forecasting frameworks. (experience)
- Familiarity with cloud/data platforms (e.g., Databricks/Azure/AWS equivalents) and modern analytics workflows. (experience)
- Experience setting standards, leading cross-functional work, and building repeatable playbooks. (experience)
- Strong hands-on capability in Python or R, plus SQL; comfortable with large datasets and model lifecycle basics. (experience)
- Excellent communication and interpersonal skills, with the ability to engage stakeholders at all levels. (experience)
- Proven expertise in statistical techniques (e.g. distributions, statistical testing, regression, etc.) (experience)
- Working knowledge in related tools and applications (e.g., Oracle, JDE, Concur, Salesforce.com) preferred (experience)
- Strict attention to detail (experience)
- Extensive knowledge and understanding of principles, theories, and concepts relevant to Artificial Intelligence (AI) and/or Machine Learning model development, and/or Control Systems. (experience)
- Experience with planning platforms (e.g., Anaplan) and driver-based planning / forecasting frameworks. (experience)
- Familiarity with cloud/data platforms (e.g., Databricks/Azure/AWS equivalents) and modern analytics workflows. (experience)
- Experience setting standards, leading cross-functional work, and building repeatable playbooks. (experience)
- Aligning our overall business objectives with performance, we offer competitive salaries, performance-based incentives, and a wide variety of benefits programs to address the diverse individual needs of our employees and their families.For California (CA), the base pay range for this position is $145,000 to $205,000 (highly experienced).The pay for the successful candidate will depend on various factors (e.g., qualifications, education, prior experience). Applications will be accepted while this position is posted on our Careers website. (experience)
Responsibilities
- Build and maintain data-driven forecasting models (time-series, AI/ML, causal/driver-based, Monte Carlo / probabilistic scenarios) for key financial and operational outcomes (revenue, margin, opex, cash flow, etc.)
- Act as a strategic partner to the Anaplan planning program: define requirements for data-based forecasting and ensure outputs integrate cleanly into planning workflows.
- Build “last mile” adoption: templates, dashboards, documentation, and stakeholder training so teams can consistently use the statistical outputs in planning and reviews.
- Communicate complex findings clearly: concise executive narratives, visuals, and recommendations grounded in data.
- Establish model testing/validation routines (back-testing, error metrics, drift monitoring) and create clear documentation for assumptions, limitations, and controls.
- Partner with FP&A to marry insights from management forecasts with data-driven insights from the statistical forecasts.
- Design scenario and sensitivity frameworks that quantify tradeoffs, risks, and uncertainty translating outputs into actionable insights for Finance and business leaders.
- Stand up an Advanced Forecasting Center of Excellence: modeling standards, reusable code/modules, data definitions, governance, and prioritization intake.
- Collaborate with Data/IT to improve pipelines, data quality/governance, and automation; ensure models are scalable, maintainable, and auditable.
- Other incidental duties
- Build and maintain data-driven forecasting models (time-series, AI/ML, causal/driver-based, Monte Carlo / probabilistic scenarios) for key financial and operational outcomes (revenue, margin, opex, cash flow, etc.)
- Act as a strategic partner to the Anaplan planning program: define requirements for data-based forecasting and ensure outputs integrate cleanly into planning workflows.
- Build “last mile” adoption: templates, dashboards, documentation, and stakeholder training so teams can consistently use the statistical outputs in planning and reviews.
- Communicate complex findings clearly: concise executive narratives, visuals, and recommendations grounded in data.
- Establish model testing/validation routines (back-testing, error metrics, drift monitoring) and create clear documentation for assumptions, limitations, and controls.
- Partner with FP&A to marry insights from management forecasts with data-driven insights from the statistical forecasts.
- Design scenario and sensitivity frameworks that quantify tradeoffs, risks, and uncertainty translating outputs into actionable insights for Finance and business leaders.
- Stand up an Advanced Forecasting Center of Excellence: modeling standards, reusable code/modules, data definitions, governance, and prioritization intake.
- Collaborate with Data/IT to improve pipelines, data quality/governance, and automation; ensure models are scalable, maintainable, and auditable.
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