Data Scientist, Consumer Analytics
New
J
JobgetherMarketing Analytics
This is a fully remote role available to employees based in the United StatesFull-TimeSenior
Salary$125,900–$201,100 in California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington State, and Washington, DC. $119,600–$191,000 in Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia.
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Job Details
- Experience
- 5+ years
- Required Skills
- Machine LearningA/B testing
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or another quantitative discipline, or an equivalent combination of education and experience.
- 5+ years of professional experience applying data science, advanced analytics, machine learning, or a closely related discipline.
- Demonstrated experience developing and implementing end-to-end analytical or machine learning solutions, including data preparation, feature engineering, model development, validation, and operationalization.
- Strong experience working with large datasets and modern data ecosystems, including distributed data processing and/or cloud-based data platforms.
- Proven ability to collaborate with product, engineering, and business stakeholders to understand requirements, prioritize analytical work, and deliver measurable outcomes.
- Strong analytical and problem-solving skills, with the ability to break down ambiguous questions into structured analyses and actionable recommendations.
- Experience with experimentation and model evaluation techniques, such as A/B testing, backtesting, error analysis, or comparable methodologies.
- Ability to communicate complex analytical and technical findings clearly and effectively to both technical and non-technical audiences.
- Strong understanding of data quality, reproducibility, model reliability, and responsible use of data and AI.
- Comfortable working independently while contributing effectively within collaborative, cross-functional teams.
- Curious, pragmatic, and continuously learning, with the ability to adapt to evolving business priorities, analytical challenges, and technology.
Responsibilities
- Design, develop, validate, and deploy end-to-end analytical and machine learning solutions addressing moderately complex business challenges and customer use cases.
- Partner with product, engineering, and business stakeholders to transform ambiguous business questions into structured problems, testable hypotheses, clear requirements, and measurable success metrics.
- Analyze large and complex datasets to identify consumer trends, behavioral drivers, opportunities, and actionable insights that support business and product decisions.
- Build and maintain scalable data pipelines, analytical features, and machine learning models using modern data and ML technologies, with a focus on reliability, reproducibility, scalability, and production performance.
- Apply experimentation and evaluation methodologies, including A/B testing, backtesting, error analysis, and model evaluation, to measure impact and continuously improve analytical solutions.
- Translate analytical findings and technical concepts into clear recommendations for both technical and non-technical stakeholders.
- Collaborate with cross-functional teams to prioritize analytical initiatives, understand business requirements, and deliver data-driven solutions with measurable impact.
- Contribute to data science standards, documentation, reusable methodologies, and best practices across the broader analytics and data science community.
- Promote responsible and effective use of data and AI by supporting data quality, model governance, evaluation standards, and responsible analytical practices.
- Continuously explore new analytical techniques, tools, and approaches to improve the quality, usability, scalability, and business value of data products.
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