PhD Jobs Related to:

Analyzing and Interpreting Data

*This list is non-exhaustive, meant to be a starting point, and will be added to regularly. Jobs may overlap with other PhD skill categories.

SEO Strategist / Analyst

Develops and executes strategies to improve a website's visibility in search engine results (Search Engine Optimization). Researches what questions audiences are searching for, optimizes written content and technical site structure to match search intent, and interprets performance data to drive organic traffic growth.

Collects, analyzes, and interprets data about markets, customers, and competitors to guide business decisions. Designs surveys and qualitative research studies, analyzes results using statistical tools, and produces reports and presentations that give product, marketing, or strategy teams actionable insights.

Studies how diseases and health outcomes are distributed across populations and what causes them. Designs observational and interventional studies, manages large datasets, runs statistical models, and translates findings into public health recommendations or clinical guidance.

Build and maintain quantitative finance models (often FP&A - Financial Planning and Analysis, compensation analytics, or investor reporting), track KPIs, and turn messy operational data into budgets, forecasts, and decision-ready narratives for leaders.

Use advanced statistics and machine learning to answer high-impact questions, build predictive models, and create data products that improve decisions (product, engineering, R&D, or clinical).

Provide statistical leadership for biomedical studies (clinical, diagnostics, or preclinical): design studies, write analysis plans, run analyses, and produce defensible results for internal decisions and regulatory needs.

Develop computational models and analysis pipelines (often scientific or biomedical) to integrate complex datasets, test hypotheses in silico, and deliver tools and insights that guide experiments or product development. Similar to Bioinformatics but more modeling-driven.

Build and run bioinformatics workflows (NGS, multi-omics, single-cell, etc.), turn raw sequencing data into interpretable results, and maintain reproducible pipelines and infrastructure used by research or product teams. Similar to Computational Biology but more tool-oriented.

Research and build state-of-the-art ML methods (often including LLMs), prototype and evaluate models, and partner with engineering and domain experts to deploy robust ML systems or data products.

Design, build, and maintain reliable data infrastructure (pipelines, data models, storage, and governance) so analysts, scientists, and products can use trustworthy data at scale.

Turn performance or customer data into clear, decision-driving insights: build dashboards, run analyses and simple models/forecasts, and tell the story so teams act (product, go-to-market, operations). Similar to Data Analyst but focused on customer and market data.

Elicit and document requirements, analyze processes and data, and bridge stakeholders and technical teams to deliver improvements (products, systems, operations, or strategy).

Use statistical and mathematical modeling to evaluate risk, price assets, optimize portfolios or strategies, and build analytics tools for investing, trading, or risk management.

Turns complex, messy data into decisions by building reliable datasets, analyzing them with appropriate statistical methods (sometimes including experimentation), and communicating insights through dashboards, writeups, and presentations.

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PhD Jobs Related to:

Analyzing and Interpreting Data

SEO Strategist / Analyst

Market Research Analyst

Epidemiologist

Studies how diseases and health outcomes are distributed across populations and what causes them. Designs observational and interventional studies, manages large datasets, runs statistical models, and translates findings into public health recommendations or clinical guidance.

Financial Analyst

Build and maintain quantitative finance models (often FP&A - Financial Planning and Analysis, compensation analytics, or investor reporting), track KPIs, and turn messy operational data into budgets, forecasts, and decision-ready narratives for leaders.

Data Scientist

Use advanced statistics and machine learning to answer high-impact questions, build predictive models, and create data products that improve decisions (product, engineering, R&D, or clinical).

Biostatistician

Provide statistical leadership for biomedical studies (clinical, diagnostics, or preclinical): design studies, write analysis plans, run analyses, and produce defensible results for internal decisions and regulatory needs.

Computational Scientist

Develop computational models and analysis pipelines (often scientific or biomedical) to integrate complex datasets, test hypotheses in silico, and deliver tools and insights that guide experiments or product development. Similar to Bioinformatics but more modeling-driven.

Bioinformatician

Build and run bioinformatics workflows (NGS, multi-omics, single-cell, etc.), turn raw sequencing data into interpretable results, and maintain reproducible pipelines and infrastructure used by research or product teams. Similar to Computational Biology but more tool-oriented.

Machine Learning Scientist

Research and build state-of-the-art ML methods (often including LLMs), prototype and evaluate models, and partner with engineering and domain experts to deploy robust ML systems or data products.

Data Engineer

Design, build, and maintain reliable data infrastructure (pipelines, data models, storage, and governance) so analysts, scientists, and products can use trustworthy data at scale.

Insights Analyst

Turn performance or customer data into clear, decision-driving insights: build dashboards, run analyses and simple models/forecasts, and tell the story so teams act (product, go-to-market, operations). Similar to Data Analyst but focused on customer and market data.

Business Analyst

Elicit and document requirements, analyze processes and data, and bridge stakeholders and technical teams to deliver improvements (products, systems, operations, or strategy).

Quantitative Analyst

Use statistical and mathematical modeling to evaluate risk, price assets, optimize portfolios or strategies, and build analytics tools for investing, trading, or risk management.

Data Analyst

Turns complex, messy data into decisions by building reliable datasets, analyzing them with appropriate statistical methods (sometimes including experimentation), and communicating insights through dashboards, writeups, and presentations.

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