(USA) Senior Manager, Data Science

About the Role

Key Responsibilities

• Provide recommendations to business stakeholders to solve complex business issues and develop business cases with projected ROI or cost savings, aligning solutions with wellbeing philosophies.
• Develop and implement robust research designs, including qualitative and quantitative approaches, and conduct observational studies to generate insights for data-driven decision-making.
• Generate graphical representations of data and model outcomes, collaborating with UX/UI designers to build front-end applications.
• Select and develop variables and features for complex problems involving large-scale, structured, and unstructured data sets, and conduct exploratory data analysis to identify trends.
• Apply best practice techniques for model testing, tuning, assessment, and validation to ensure accuracy, fit, and robustness of multistage models and ensembles.
• Deploy models to production, monitor model behavior, and identify parameters needing modifications based on deployment scale.
• Create audience-tailored content and utilize data visualization tools to communicate complex analytical insights effectively to both technical and non-technical stakeholders.

Requirements

• Experience in health economics or equivalent organizational/social research methods, including cost-effectiveness/ROI analysis, health outcome modeling, and resource allocation/optimization/simulation models.
• Proficiency in data visualization tools and programming libraries such as Python, R (GGplot, Matplotlib, Plotly), Tableau, PowerBI.
• Knowledge of advanced statistical methods, machine learning algorithms, and optimization techniques like Linear Programming, Integer Programming, Quadratic Programming.
• Experience with coding languages including SQL, Java, C, Python, and testing methods.
• Business acumen across domains such as product, finance, marketing, sales, technology, and human resources, with the ability to translate business needs into data science solutions.
• Strong willingness to explore new methodologies, tools, and technologies for data source exploration and feature engineering, with knowledge of ML operations.
• Ability to communicate insights clearly and adapt communication style based on stakeholder guidance.

Nice to Have

• Experience in data science, machine learning, and optimization models.
• PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics.
• Successful completion of assessments in Python, Spark, Scala, or R.
• Supervisory experience.
• Experience with open source frameworks such as scikit-learn, TensorFlow, Torch.
• Background in creating inclusive digital experiences and knowledge of Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and digital accessibility best practices.

Qualifications

• Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
• Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
• Option 3: 7 years' experience in an analytics or related field.

Benefits & Perks

• Competitive pay, performance-based incentive awards, and other benefits.
• Health benefits including medical, vision, and dental coverage.
• Financial benefits such as 401(k), stock purchase, and company-paid life insurance.
• Paid time off including PTO, sick leave, parental leave, family care leave, bereavement, jury duty, and voting.
• Other benefits like short-term and long-term disability, education assistance, company discounts, military service pay, adoption expense reimbursement.
• Live Better U education benefit program covering tuition, books, and fees.