// hire - data science
Hire data scientists who turn data into decisions.
Not a slide deck of correlations — analysts and modelers who join your team, work against your own data, and hand off findings your business can actually act on.
- Data scientists
- Predictive modeling specialists
- Statistical analysts
- Data visualization engineers
- Data science consultants
- Experimentation & A/B test analysts
// build your team
Tell us what you're building
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definition
What does it mean to hire a data scientist?
A dedicated data scientist is an analyst who joins your team on a defined engagement, works against your own data and business questions, and owns model and analysis outcomes the way an in-house hire would.
key takeaways
Syndell's data scientists work in Python and R for modeling, with Power BI and Tableau for the reporting layer stakeholders actually see.
Analysis pairs naturally with our AI/ML and data engineering practices, so a predictive model can move from notebook to production without changing teams.
Engagements are drawn from a bench built across 1,500+ delivered projects, so a shortlist is usually ready within days, not weeks of sourcing.
Syndell's engineering studio is based in Ahmedabad, India, serving businesses across the US, UK, Australia, Canada, and UAE, with a guaranteed daily overlap window against your working hours.
// why analysis alone isn't the deliverable
A data scientist who hands you a report and moves on has done half the job. The harder part is making the finding usable: a churn model that a sales team can actually query, a forecast that plugs into planning instead of sitting in a slide, a dashboard built for the question a stakeholder keeps asking instead of the one that was easiest to chart. An embedded hire stays accountable for that last step, because they're on your team, not a vendor with a signed-off deliverable.
capabilities - seven
What your data science hire can own.
From use-case scoping through production handoff — pick the slice you need.
- 01Predictive model development
Models trained on your own historical data, built to answer a specific business question, not a generic forecasting demo.
- 02Statistical analysis & experimentation
A/B testing and causal analysis designed so you can trust the result before you act on it.
- 03Data visualization & reporting
Dashboards in Power BI or Tableau that answer the question a stakeholder actually asked, not a wall of charts nobody reads.
- 04Use-case scoping & consulting
A feasibility pass before any modeling starts, so you know what your data can and can’t support.
- 05Model deployment handoff
Analysis handed off in a form your engineering team can actually put into production, not a notebook that only runs on one laptop.
- 06Data pipeline collaboration
Close coordination with data engineering so the pipeline feeding a model is as reliable as the model itself.
- 07Support & iteration
Ongoing model review and retraining as your data and business change, priced into the engagement instead of a surprise later.
how it works
Four steps to an embedded data scientist.
- 01
Scope the role
Data maturity, the question you need answered, and the outcome the hire owns. One call is usually enough to size it.
- 02
Meet vetted candidates
Pre-screened data scientists from our bench — you interview them exactly like your own hires.
- 03
Trial the fit
A working period where you evaluate real analysis on real data before committing to the full engagement.
- 04
Confirm and embed
The data scientist joins your backlog, your standups, and your reporting cadence, with a guaranteed daily overlap window.
tools our data scientists work in
- Python
- R
- Pandas
- scikit-learn
- Power BI
- Tableau
- Jupyter
- SQL
-- the bench you're hiring from --
years of experience
projects delivered
happy clients
countries served
client recommendation
engagement
Which engagement model fits you?
| Dedicated data scientist | Hourly engagement | Fixed-scope build | |
|---|---|---|---|
| Best for | Ongoing modeling and analysis across the business | A defined block of analysis or model work | A single model or report with a clear finish line |
| You get | A named data scientist embedded full-time in your team | Flexible hours against a scoped deliverable | A scoped deliverable with an agreed timeline |
| Timeline | Monthly, renews | Weeks to a few months | Project-length |
No pricing tables here on purpose — seniority, scope, and data maturity drive cost, and a real number after one call beats a misleading one now. Tell us what you're building.
frequently - asked
Five questions,
straight answers.
01What does it cost to hire a dedicated data scientist?
It depends on seniority, engagement model, and whether the work is analysis, modeling, or both. We don't publish rate cards because scope drives cost too much for a number to mean anything on its own — book a call and you'll get a concrete estimate against your actual data.
02Will my data scientist overlap with my working hours?
Yes. Every embedded data scientist commits to a guaranteed live overlap window with your team every working day, alongside async standups and reporting.
03What tools do your data scientists work in?
Python and R for analysis and modeling, Power BI and Tableau for visualization and reporting, and SQL against whatever warehouse or database you already run.
04Can your team take over an incomplete data science project?
Yes. We start with a short assessment of the existing data, models, and assumptions so you know what is salvageable before committing to a rebuild versus a continuation.
05Can data science support marketing and SEO decisions?
Yes. Keyword and demand forecasting, content gap identification, and campaign performance modeling are common requests once the core analysis work is running.
build the team
Explore other roles you can hire.
- All developer teams
every role Syndell staffs, from AI/ML to Shopify
- Hire AI/ML developers
take a validated model into production
- Hire data engineers
the pipelines that feed the analysis your data scientist runs
- Hire an AI marketing specialist
turn analysis into campaigns that act on it
- Hire full-stack developers
ship the dashboards and tools your data scientist designs
- AI consulting services
the practice this hire draws on for use-case scoping and delivery
Comparing agencies before you commit? Browse the work our teams have shipped or read our full services overview.
