Data Scientist - Cork, Ireland at AtData
Cork, County Cork, Ireland -
Full Time


Start Date

Immediate

Expiry Date

05 Dec, 25

Salary

0.0

Posted On

06 Sep, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Agile Methodologies, Optimization, Text Analytics, Sql, Computer Science, Mathematics, Hypothesis Testing, Scrum, Business Applications, Graph Theory, Machine Learning, Database Administration, Data Cleaning, Data Science, Kanban

Industry

Information Technology/IT

Description

Job Description:

REQUIREMENTS

  • Bachelor’s degree or higher in data science, mathematics, computer science, or a related field.
  • Minimum 3 years’ experience as a Data Scientist or in a comparable data analytics role.
  • Deep understanding of key data science concepts: machine learning, data cleaning, bias detection, graph theory, hypothesis testing, univariate/multivariate analysis, optimization, and text analytics.
  • Proficient in SQL and NoSQL database querying techniques.
  • Skilled in at least one programming language, ideally Python or R.
  • Comfortable with source control tools (e.g., Git) and collaborative development workflows.
  • Strong communication and documentation capabilities.

PREFERRED QUALIFICATIONS

  • Experience in database administration.
  • Knowledge of Agile methodologies such as Scrum or Kanban.
  • Practical experience implementing Large Language Models (e.g., GPT) in business applications.
  • Competency in Microsoft Office suite.
Responsibilities

ROLE SUMMARY

AtData seeks a proactive Data Scientist who excels in a dynamic environment. You will uncover insights from billions of signals, architect models behind our APIs, and collaborate cross-functionally to translate concepts into real-world features for major brands.

CORE RESPONSIBILITIES

  • Analyse large-scale datasets (email, identity, transaction) to generate actionable business insights.
  • Design, implement, and maintain statistical and machine learning models for APIs and offline solutions.
  • Partner with engineering and product teams to define requirements and launch impactful features.
  • Manage and optimize data assets such as tables, indices, and data repositories.
  • Create and publish insights through whitepapers, blog articles, and presentations.
  • Apply empirical methods to assess and project the business impact of new features and science-driven initiatives.
    Experience and Skills:
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