Data Scientist — Web and Content Analytics

About the role

We are hiring a Data Scientist to turn complex web datasets into clear, repeatable decisions. You will work with the Head of Growth and the Client Strategy team to frame the right questions, run focused analyses, and recommend actions that drive measurable impact. The work blends analytics, light engineering, and practical research.

Responsibilities

• Build topic clusters from keyword sets and map them to canonical pages. Propose internal link updates tied to measurable goals.
• Produce rankings and visibility snapshots from Search Console, SERP, and backlink data. Translate findings into prioritized actions.
• Collect and validate citations for content. Maintain lightweight sourcing standards and keep noise out.
• Monitor indexing and crawl efficiency using coverage reports, sitemaps, and where available, logs. Surface crawl sinks and orphaned pages.
• Develop small, reproducible scripts in Python and SQL for API pulls, batching, retries, and clean CSV outputs.
• Apply appropriate statistics for rank-like data. Use Spearman and consider log transforms for heavy-tailed metrics. Document assumptions.
• Write short briefs that quantify expected impact and outline the first actions to take.

Research ability and AI adaptability

• Design small investigations that compare approaches and recommend a path with trade-offs made explicit. Examples include co-citation patterns, domain neighborhoods, and entity sourcing.
• Use modern AI tools where they help. Typical uses include entity extraction, citation triage, and light enrichment. Evaluate results against ground truth and keep prompts and configs versioned.
• Choose simple, robust methods first. Escalate to ML or graph techniques only when they improve signal in a meaningful way.
• Dynamic work environment.

Required Qualifications

• Two or more years working with web or content performance datasets. Examples include Search Console, SERPs, backlinks, sitemaps, or logs.
• Proficiency in Python and SQL. Comfortable with notebooks or scripts, virtual environments, and config files.
• Experience with APIs or light scraping that handles rate limits, retries, and basic logging.
• Ability to communicate findings in clear language with quantified, testable recommendations.

Preferred

• Practical experience with clustering methods or simple graph reasoning for co-mentions and authority.
• Exposure to evaluating outputs from LLMs and setting basic guardrails.

How you will work

• Deliver small, well-scoped analyses that produce reusable artifacts such as clusters, link recommendations, citation lists, and crawl fixes.
• Use config-driven scripts and idempotent outputs so work can be re-run by others.
• Apply the right level of rigor. Use the correct metric for the data, keep overhead low, and document decisions.

Tools

Python, SQL, lightweight APIs for search and web data, simple scraping libraries, and Looker Studio or similar for quick views. Clean text outputs and CSVs are preferred over complex dashboards, DataForSEO (or equivalent APIs).

Compensation and working model

• Salary from $1,900 USD per month
• Fully remote and async-first
• High autonomy with clear ownership and paths into senior data strategy, analytics, or R&D

Working hours

• Fully remote position
• Flexible schedule, async-first collaboration

What's on offer

• Work alongside and learn from high-caliber colleagues
• Strong career development opportunities
• Attractive salary and benefits