Escalent is an award-winning data analytics and advisory firm that helps clients understand human and market behaviors to navigate disruption. The Senior Data Scientist will lead complex analytical workstreams, apply robust statistical methodologies, and contribute to actionable insights across client engagements.
Responsibilities:
- Design and execute statistical models, including:
- Regression and multivariate analysis
- Segmentation and clustering techniques
- Choice modeling and conjoint analysis
- Lead model estimation, validation, and interpretation for assigned workstreams
- Ensure analytical approaches are rigorous, scalable, and aligned to study objectives
- Translate business and research questions into structured analytical approaches
- Lead key components of analysis within client projects, partnering with senior team members on overall strategy
- Contribute to development of insights that are clear, actionable, and aligned to client needs
- Prepare, transform, and validate survey and panel datasets
- Apply data quality checks, weighting, and standard processing techniques
- Develop efficient workflows to support repeatable and scalable analysis
- Partner with research and client teams to align on study objectives and outputs
- Translate analytical findings into clear summaries for internal and client-facing use
- Support development of deliverables and presentations that communicate insights effectively
- Follow and help reinforce standards for coding, documentation, and reproducibility
- Participate in knowledge sharing and continuous improvement efforts
- Provide informal guidance to junior team members as appropriate
- Apply synthetic data techniques to support research design, modeling, and data augmentation
- Ensure appropriate use of synthetic datasets while maintaining analytical integrity and validity
- Contribute to expanding team capabilities and best practices in synthetic data applications
Requirements:
- 4–8 years of experience in data science, applied statistics, or market research analytics
- Strong proficiency in R or Python for data analysis and modeling
- Demonstrated experience with: Regression and multivariate analysis
- Demonstrated experience with: Segmentation techniques (e.g., clustering)
- Demonstrated experience with: Choice modeling / conjoint analysis
- Demonstrated experience with: Application of synthetic data in analytics workflows or research contexts
- Experience working with survey, panel, or behavioral datasets
- Strong problem-solving skills and attention to detail
- Ability to clearly communicate analytical findings to non-technical audiences
- Experience in market research, consulting, or client-facing analytics environments
- Familiarity with experimental design or causal inference methodologies
- Experience contributing to multi-phase or complex client engagements
- Have experience or exposure to algorithms capable of generating synthetic data