Conduct research and develop Media Mix Modeling algorithms using statistical, econometric, Bayesian, and causal inference methods. Work with time-series, panel, and marketing data; build models end-to-end; develop diagnostics and validation frameworks; run simulations; compare methodologies; and translate research into production-ready analytical solutions. Collaborate with senior data scientists on real client datasets and document methodology, assumptions, limitations, and results.
Duration: 3 months
Employment: Full-time, Paid Internship
Compensation: Based on experience
Location: Remote
Company: FocusKPI
This is a hands-on, research-oriented role for someone with a strong foundation in statistics, econometrics, economics, or a closely related quantitative discipline who is interested in applying rigorous statistical methodology to real-world marketing and business problems.
The ideal candidate will have deep theoretical knowledge combined with practical experience developing statistical models end-to-end—from problem formulation and data preparation through model development, validation, interpretation, and production implementation.
The intern will work closely with senior data scientists and leadership to evaluate and enhance our MMM methodology, explore new modeling approaches, and translate advanced statistical techniques into scalable analytical solutions.
Employment: Full-time, Paid Internship
Compensation: Based on experience
Location: Remote
Company: FocusKPI
About the Role
FocusKPI is seeking a highly motivated PhD Data Science Intern to join our team for a three-month, full-time engagement focused on the research, development, and advancement of Media Mix Modeling (MMM) algorithms.This is a hands-on, research-oriented role for someone with a strong foundation in statistics, econometrics, economics, or a closely related quantitative discipline who is interested in applying rigorous statistical methodology to real-world marketing and business problems.
The ideal candidate will have deep theoretical knowledge combined with practical experience developing statistical models end-to-end—from problem formulation and data preparation through model development, validation, interpretation, and production implementation.
The intern will work closely with senior data scientists and leadership to evaluate and enhance our MMM methodology, explore new modeling approaches, and translate advanced statistical techniques into scalable analytical solutions.
What You Will Do
- Research and evaluate statistical and econometric approaches for Media Mix Modeling and marketing effectiveness measurement
- Develop, test, and enhance MMM algorithms across the full modeling lifecycle
- Work with time-series, panel, and observational marketing data to develop robust models of media response and business outcomes
- Media response curves and saturation effects
- Adstock and carryover effects
- Incrementality and causal inference
- Channel interaction and synergies
- Seasonality, trends, and external factors
- Model regularization and variable selection
- Uncertainty estimation and statistical inference
- Bayesian and frequentist modeling approaches
- Develop model diagnostics and validation frameworks to assess model stability, predictive performance, statistical significance, and business interpretability
- Conduct simulation and experimentation to understand algorithm behavior under different data-generating conditions
- Compare alternative modeling methodologies and identify opportunities to improve model accuracy, robustness, and interpretability
- Translate research findings into production-ready algorithms and analytical workflows
- Work with real client datasets and understand the practical challenges of applying MMM to imperfect business data
- Collaborate with senior data scientists to document methodology, assumptions, limitations, and results
- Contribute to the development of next-generation MMM capabilities within FocusKPI
Required Qualifications
- PhD in Statistics, Economics, Econometrics, Applied Mathematics, Data Science, or a closely related quantitative field
- Statistical modeling
- Econometrics
- Regression and multivariate analysis
- Time-series analysis
- Probability and statistical inference
- Optimization
- Strong understanding of causal inference and observational data
- Problem formulation
- Data preparation and feature engineering
- Model specification
- Estimation
- Model diagnostics
- Validation
- Interpretation
- Implementation
- Strong programming skills in Python
- Experience working with large, complex datasets
- Ability to translate mathematical and statistical concepts into practical algorithms
- Strong analytical and problem-solving skills
- Ability to work independently while collaborating closely with senior technical team members
Preferred Qualifications
- Direct experience with Media Mix Modeling (MMM)
- Experience with marketing measurement, marketing analytics, or advertising data
- Experience with Bayesian hierarchical models
- Experience with causal inference, experimentation, or uplift modeling
- Experience with time-series econometrics
- Bayesian inference / MCMC
- State-space models
- Regularization
- Constrained optimization
- Nonlinear regression
- Response curve estimation
- Monte Carlo simulation
- Experience with modern statistical computing frameworks such as PyMC, Stan, NumPyro, JAX, scikit-learn, statsmodels, or equivalent
- Experience taking research concepts and converting them into reusable production code
focuskpi Santa Clara, California, USA Office
1800 Wyatt Dr, Santa Clara, CA, United States, 95054
focuskpi San Francisco, California, USA Office
San Francisco, United States
focuskpi San Jose, California, USA Office
San Jose, United States
Similar Jobs
Consumer Web • Healthtech • Professional Services • Social Impact • Software
Build and mature Headway’s infrastructure security program across AWS and application platforms. Partner with Product and Infrastructure teams on secure system design, security reviews, platform guardrails, vulnerability remediation, and continuous infrastructure improvement. Support incident response and security operations while advancing AI-native cloud security practices. The role requires strong technical depth, cross-functional collaboration, and the ability to establish secure-by-default engineering practices in an ambiguous, fast-paced environment.
Top Skills:
Amazon EcsAmazon S3AnthropicAWSAws FargateCloudflareCursorDatadogFastapiGitKubernetesLangsmithPagerdutyPostgresPython 3ReactRedisSemgrepSqlalchemyTypescriptWiz
Consumer Web • Healthtech • Professional Services • Social Impact • Software
Drive complex cross-functional initiatives, identify operational opportunities, build scalable workflows, analyze data, and deliver measurable improvements. The role owns initiatives from scoping through execution, coordinates stakeholders without formal authority, designs scalable systems and processes, and provides structured recommendations to support pod and organizational priorities.
Top Skills:
Ai ToolsDashboardsExcelLookerSQL
Artificial Intelligence • Fintech • Hardware • Information Technology • Sales • Software • Transportation
Plan, execute, and optimize multi-channel B2B demand generation and ABM campaigns for the mid-market segment. Partner with content, product marketing, marketing operations, sales, and analytics teams to align targeting, messaging, enablement, and pipeline goals. Manage webinars, sales plays, direct mail, and other channels; monitor performance, conduct testing, optimize spend, maintain reporting, and translate campaign data into actionable recommendations. Use AI tools to improve personalization and execution.
Top Skills:
6SenseAi ToolsAsanaClayExcelGleanGoogle SheetsLinkedInMarketoOutreachSalesforceSendosoTableau
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
