Senior Manager, Data Science

Alcon•Fort Worth, TX

22h•Onsite

About The Position

At Alcon, we are driven by the meaningful work we do to help people see brilliantly. We innovate boldly, champion progress, and act with speed as the global leader in eye care. Here, you’ll be recognized for your commitment and contributions and see your career like never before. Together, we go above and beyond to make an impact in the lives of our patients and customers. We foster an inclusive culture and are looking for diverse, talented people to join Alcon. As a Senior Manager, Data Science, you will be trusted to lead and develop a high-performing Data Science team while driving advanced analytics, predictive modeling, statistical analysis, traditional Machine Learning, and Artificial Intelligence solutions across the organization. This role will lead a balanced portfolio of enterprise analytics initiatives spanning forecasting, optimization, predictive analytics, machine learning, and Generative AI capabilities. Based in Fort Worth, Texas, this onsite role partners closely with business and technology stakeholders to deliver actionable insights, support strategic decision-making, and advance enterprise analytics capabilities. You will lead high-impact initiatives involving statistical modeling, predictive analytics, cloud-based AI platforms, Generative AI, and analytics translation while helping to shape scalable data science solutions across Commercial, Supply Chain, Manufacturing, and other enterprise functions. This role offers the opportunity to influence business strategy, foster innovation, and deliver measurable business impact through responsible AI, data governance, and advanced analytics practices.

Requirements

Bachelor’s Degree or Equivalent years of directly related experience (or high school +15 yrs; Assoc.+11 yrs; M.S.+4 yrs; PhD+3 yrs)
7 Years of Relevant Experience
5 Years of Demonstrated Leadership
The ability to fluently read, write, understand and communicate in English

Nice To Haves

Master's degree in Data Science, Analytics, Computer Science, Business Administration, Statistics, Engineering, or a related field.
Experience leading Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics initiatives.
Strong analytical thinking, technical problem-solving, and data-driven decision-making skills.
Extensive experience developing, validating, deploying, and monitoring Machine Learning and statistical models in production environments, including predictive modeling, forecasting, classification, regression, clustering, optimization, and experimentation techniques.
Experience with Python, SQL, AWS, SageMaker, Bedrock, Azure AI, or similar cloud-based analytics and AI platforms.
Strong knowledge of Machine Learning, MLOps, model governance, feature engineering, model validation, responsible AI practices, and experience applying these principles in enterprise-scale environments.
Experience managing data pipelines, model maintenance, model monitoring, and production analytics solutions.
Experience leading, mentoring, and developing Data Science teams.
Strong stakeholder management, business partnership, and executive communication skills.
Experience supporting Commercial, Sales, Marketing, Supply Chain, Manufacturing, or Digital Transformation initiatives through analytics

Responsibilities

Formulating, recommending and managing data-driven projects which are geared at furthering the business's interests.
Collaborate with Data Strategy team to collect, prepare, and transform data from multiple sources to support analytics and AI initiatives.
Selecting and applying advanced statistical procedures to obtain actionable insights.
Validating, testing, and cross-validating models to ensure accuracy, scalability, and business applicability.
Leading and mentoring Data Scientists and Analysts while delegating priorities to support the successful delivery of key initiatives.
Producing and communicating non-technical reports and presentations that clearly articulate project outcomes, opportunities, limitations, and business impact through effective analytics translation.
Partnering with stakeholders to identify opportunities where insights and advanced analytics can inform business strategy and decision-making.
Staying informed on emerging trends and advancements in Data Science, Artificial Intelligence, Machine Learning, Generative AI, and related technologies to ensure solutions remain relevant and innovative.
Guiding architecture decisions related to AI platforms, cloud infrastructure, data pipelines, and enterprise analytics capabilities.
Applying LLMOps principles, including model lifecycle management, observability, experimentation, governance, guardrails, and continuous improvement practices.
Supporting the implementation and operationalization of AI and Generative AI solutions utilizing cloud-based platforms such as AWS Bedrock, Azure AI, OpenAI, and related technologies.
Apply a deep understanding of Generative AI, Agentic AI, and LLMOps demonstrated experience developing enterprise-scale AI solutions that leverage foundation models, knowledge retrieval, orchestration frameworks, and business workflow automation.
Establish governance, security, compliance, and performance monitoring frameworks for production GenAI solutions while ensuring scalability, reliability, and measurable business impact
Ensure solutions adhere to MLOps, governance, validation, risk management, and compliance standards.
Mentoring and developing a high-performing data science team while delivering impactful use cases across Sales, Marketing, Supply Chain Manufacturing and other enterprise functions.