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Codemotives

AI & Data Talent

Hire Data Scientists

Our data scientists explore your data, test hypotheses and build models, then explain what they found in terms your business can act on.

Get in touchHow we work

Overview

Hire Data Scientists

Data scientists combine statistics, programming and domain curiosity. They examine your data, find patterns and anomalies, test ideas rigorously, and build models where prediction is useful. Just as important, they communicate: charts, summaries and recommendations that decision makers can understand without a statistics background. The work is shaped by your goals, your existing code and the way your team already plans and reviews its work.

We start from the question you are trying to answer, not the algorithm. If your data cannot support the question yet, we tell you what is missing. Engagements can be dedicated, part-time or project-based, and our data scientists work alongside your engineers so findings can reach production. We keep the scope practical and explain trade-offs in plain language, so decisions stay in your hands.

Context

When to hire

  • 01

    Decisions rely on gut feeling

    You have data but no one dedicated to extracting evidence from it.

  • 02

    Reports exist but insights do not

    Dashboards show what happened, not why, or what is likely next.

  • 03

    You need a one-off analysis

    A pricing study, cohort analysis or forecast needs expertise for a limited time.

  • 04

    Data is messy and scattered

    Spreadsheets, databases and exports need cleaning and joining before they are useful.

Capabilities

Skills you get

  1. 01

    Exploratory analysis

    Profile datasets, find quality issues and surface patterns worth investigating.

  2. 02

    Statistical testing

    Design experiments and tests so conclusions are supported rather than anecdotal.

  3. 03

    Predictive modeling

    Build forecasting, classification and segmentation models with honest validation.

  4. 04

    Data cleaning and pipelines

    Turn raw sources into consistent, documented datasets.

  5. 05

    Visualization and storytelling

    Present results clearly with charts and written summaries for non-technical readers.

  6. 06

    Handover to engineering

    Package analysis as code or services your team can run and maintain.

Typical work

  • Customer segmentation
  • Sales and demand forecasting
  • A/B test analysis
  • Pricing and churn studies
  • KPI and reporting foundations

Tools they use

  • Python
  • R
  • Pandas
  • NumPy
  • scikit-learn
  • Jupyter
  • SQL
  • Tableau

Approach

How hiring works

  1. 1

    Share your needs

    Tell us about your project, stack, team setup and the skills you are looking for.

  2. 2

    Review the match

    We suggest developers whose experience fits, and you can talk with them before deciding.

  3. 3

    Onboard

    Access, tools, communication channels and working hours are agreed up front.

  4. 4

    Build & review

    Work runs in your process with regular updates, and the team can scale as needs change.

FAQs

Common questions

Have a question that is not covered here? Get in touch.

What if we are not sure our data is good enough?

We can begin with a short assessment of what you have and what the question needs. Sometimes the first deliverable is a plan to collect better data.

Will we receive code or only reports?

Usually both. Notebooks, scripts and documentation are delivered so analysis can be repeated, subject to what is agreed.

How do data scientists work with our team?

They join your communication channels, attend relevant meetings and share work in progress, so domain experts can correct assumptions early.

Who owns the analysis?

Ownership is defined in the agreement, typically assigned to the client.

Explore

Keep exploring

Let's build what's next

Tell us about your idea, product or legacy system. Send us a message and we will help you scope the right next step.

Get in touch