Hire a Fractional Data Scientist
Fractional Data Scientists. Real Decisions.
Senior data science expertise that turns your raw data into models, insights, and competitive advantage — on a flexible, part-time engagement that scales with your needs.
Why data leaders choose Fractionus
- Vetted practitioners only. We shortlist experienced Data Scientists with production track records in your industry and data environment.
- Fast start. Typical kickoff in days — no six-month PhD hiring process required.
- Flexible engagement. 1–3 days/week, day rate or retainer, scaled to your project pipeline.
- Clear outcomes. Deployed models, validated experiments, and data products your team can act on.
What is a Fractional Data Scientist?
A Fractional Data Scientist is a senior practitioner who partners with your team on a part-time basis to design, build, and deploy data science solutions to your most important business problems. They bring the statistical rigour, engineering discipline, and business acumen needed to turn your data into a real competitive asset — without requiring full-time headcount.
Where they go deep
- Predictive modelling (churn, LTV, demand forecasting, pricing)
- Machine learning model development, validation, and deployment
- Customer segmentation and behavioural analytics
- Experimentation framework design and A/B test analysis
- Natural language processing (NLP) and text analytics
- Data pipeline design, feature engineering, and ETL architecture
- Recommendation engines and personalisation systems
- Data strategy, stack assessment, and capability roadmap
Fractional CSIO
Ex-SoundCloud
Fractional CRO
Ex-Heineken
Fractional CXO
Ex-McKenzie
Fractional GTM
Ex-Salesforce
Fractional Head of AI
Ex-GE Capital
Fractional COO
Ex-Glossier
Fractional CTO
Ex-Afterpay
Fractional CTO
Ex-Google
Fractional CPO
Ex-Pleo
Fractional CTO
Ex-BMW
Fractional CPO
Ex-@ Lego
Fractional CFO
Ex-We Are Brands
When to hire a Fractional Data Scientist
- You have data but no models. Your warehouse is full and your team produces reports — but nobody is building the predictive systems that could actually change your decisions.
- You need a specific model built fast. Churn prediction, demand forecasting, customer LTV scoring — a fractional Data Scientist gets it built without a full-time hire.
- Your A/B testing is unreliable. If your experiment results are noisy or your team lacks statistical confidence, a fractional Data Scientist designs the framework to fix it.
- You’re building out a data team. A fractional Data Scientist can set technical standards, review work, and mentor junior analysts while you build out the permanent function.
- You’re preparing for a fundraise. Investors increasingly expect data-driven unit economics and forecasts — a fractional Data Scientist builds the models and validates the numbers.
What does engagement look like?
Most companies engage a fractional Data Scientist on a project basis or monthly retainer of 1–3 days per week, depending on the complexity and urgency of the work. Common formats: sprint-based model builds, ongoing analytics retainers, or embedded team support.
90-Day deliverables typically include
- Data audit and opportunity prioritisation
- First deployed predictive model (churn, LTV, demand, or similar)
- Experimentation framework and statistical testing standards
- Customer segmentation model and cohort analysis
- Data stack assessment and recommendations
- Documentation and handover so your team can maintain the work
Hire a Fractional Data Scientist
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Why the fractional model is surging
Senior Data Scientists with production deployment experience command $180K–$250K+ in full-time roles — and the talent pool is genuinely thin. Most businesses don’t need a full-time data scientist five days a week; they need the right models built right. The fractional model closes that gap perfectly, giving companies access to world-class data science expertise at the stage and budget that actually makes sense.
How Fractionus works
- Brief us once. Your data environment, the problems you’re trying to solve, your stack, and your team.
- Shortlist in days. Meet 2–3 vetted fractional Data Scientists matched to your industry and technical needs.
- You choose. Interview, check fit, and select your practitioner.
- We handle everything else. Paperwork, billing, and smooth scale-up/scale-down.
What you’ll get — and measure
- Deployed models your team can run and maintain — not just notebooks
- Measurable improvement in the decisions your models support (churn reduction, forecast accuracy, conversion lift)
- A documented experimentation framework your team can follow independently
- A data capability assessment with a prioritised roadmap for what to build next
- Data products that create lasting competitive advantage, not one-off analysis
Fractional leaders from top brands
Frequently Asked Questions
Answers to the most common questions about working with a Fractional Data Scientist through Fractionus
Do we need a data engineer before hiring a data scientist?
Not necessarily. A fractional Data Scientist can work with raw data sources and build lightweight pipelines as part of their engagement. For more mature data infrastructure, they’ll assess what’s needed and can help scope the engineering work alongside their modelling work.
What data stack do your Data Scientists work with?
Our network includes practitioners experienced across Python (pandas, scikit-learn, PyTorch, TensorFlow), SQL, dbt, Snowflake, BigQuery, Databricks, and most major cloud platforms (AWS, GCP, Azure). We match based on your specific environment.
Is a fractional Data Scientist the same as a data analyst?
No. A data analyst produces reports and descriptive analytics — what happened. A Data Scientist builds predictive and prescriptive models — what will happen and what you should do about it. The roles are complementary but not interchangeable.
How quickly can we start?
Most clients meet shortlists within a week and kick off within days after selection.
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