Hire Data Scientists

Data scientists who turn messy data into measurable business outcomes

Translate ambiguous business problems into clear analytical questions and hypotheses
Design, validate, and deploy models that improve decisions, automation, and customer experience
Embed with your teams to move from dashboards and PoCs to production-grade data products

When hiring a data scientist through us is a strong fit

Signals that it’s time to bring in dedicated data science capability.

You have data, but limited analytical capacity

You’re collecting significant product, customer, or operational data, but lack people who can turn it into decisions and models.

Your AI and analytics backlog keeps growing

High-value analytics and ML ideas are stuck behind day-to-day reporting and engineering priorities.

PoCs aren’t making it into production

You’ve run pilots or vendor-led experiments, but lack in-house ownership to harden, monitor, and evolve them.

You need clearer metrics for product and operations

Teams are debating opinions instead of working from well-defined metrics, experiments, and causal analysis.

You want to de-risk strategic AI initiatives

You’re planning major investments in AI or data platforms and need senior data science input on feasibility and value.

Hiring permanent data scientists is slow or costly

You need senior capability now, with the option to scale up or down without committing to long recruitment cycles.

What our data scientists deliver

High-impact work your data scientist can own

SaaS / Subscription

Customer churn prediction and retention levers

Build and validate churn models, identify leading indicators, and surface concrete retention actions for sales and success teams.

Retail / E‑commerce

Pricing and revenue optimisation

Analyse elasticity, seasonality, and demand drivers to recommend data-driven pricing strategies that lift margin and revenue.

Logistics / Operations

Operational forecasting and capacity planning

Develop forecasting models for volume and workload, improving staffing, inventory, and capacity decisions across the operation.

Digital Products

Experimentation and product analytics

Design A/B tests, define success metrics, and analyse behavioural data to guide roadmap decisions and feature rollout.

Financial Services / Marketplaces

Risk and fraud detection models

Create and calibrate risk scores and anomaly detection models that reduce fraud losses while minimising false positives.

How we engage

Data scientists embedded to deliver value fast

We scope the problems that matter, match you with the right data science talent, and integrate them into your teams to deliver outcomes quickly.

Clarify goals, data landscape, and constraints

We work with your stakeholders to understand business objectives, available data sources, technical stack, and regulatory constraints.

Define the role, seniority, and engagement model

We shape the data scientist profile, required domain expertise, and whether you need a single expert, a pod, or project-based delivery.

Source, vet, and match the right data scientist

We provide pre-vetted candidates with strong statistical foundations, coding skills, and communication ability, aligned to your context.

Onboard and integrate with your teams

We set up access, ways of working, and delivery cadence so your data scientist collaborates effectively with engineering, product, and business leads.

Deliver, iterate, and scale impact

We focus on shipping models, insights, and decision tools, with regular reviews, performance tracking, and the option to expand or transition the team.

Business Outcomes

Data science capacity that aligns with your roadmap without long hiring cycles.
Models and insights that are explainable, robust, and usable by the business.
Faster path from data exploration to production-grade data products.
Reduced risk of stalled PoCs and orphaned dashboards.

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