AI Data Scientist

5 hours, 52 minutes ago
Full-time
Mid Level
Data Science and Analytics
AIRTM

AIRTM

Airtm: Empowering digital entrepreneurs & gig workers with a borderless platform for money transfers, offering 500+ payment methods for instant, commission-free transactions.

Internet Software & Services
51-250
Founded 2015
$25M raised

Description

  • Design and deploy AI agent workflows to automate recurring analytical tasks, data summarization, and insight generation pipelines.
  • Evaluate and integrate LLM-based tools into the data team's workflow and assess their reliability, accuracy, and analytical fitness.
  • Collaborate with product and business teams to define analytical questions, success metrics, and KPIs.
  • Build and maintain the analytics foundation using SQL and dbt to enable reliable reporting and self-serve analytics.
  • Design, build, and maintain Tableau dashboards to support day-to-day decision-making.
  • Perform A/B testing and experimentation, including experiment design, statistical inference, significance testing, and result interpretation.
  • Conduct ad-hoc, exploratory, and statistical analyses to uncover insights and validate hypotheses.
  • Communicate findings clearly to technical and non-technical stakeholders and translate data into actionable recommendations.
  • Partner with stakeholders to iterate on metrics, dashboards, and analyses as business needs evolve.

Requirements

  • 2 to 5 years of experience in similar roles.
  • Hands-on experience with AI agent frameworks such as LangChain, LlamaIndex, CrewAI, or similar.
  • Demonstrated ability to build and deploy agentic systems in a production or near-production context.
  • Proven experience with prompt engineering and evaluating LLM outputs for data-related tasks.
  • Experience orchestrating multi-step AI pipelines that combine LLMs with structured data sources, APIs, or internal tooling.
  • Strong SQL and Python skills for data analysis and modeling.
  • Experience with dbt for analytics engineering workflows.
  • Experience building dashboards in Tableau or similar BI tools.
  • Solid foundation in statistics, experimentation, and hypothesis testing.
  • Ability to work cross-functionally and communicate insights effectively.
  • Exposure to cloud platforms such as AWS for data storage or analytics workloads, preferred.
  • Knowledge of feature engineering and model evaluation concepts, preferred.
  • Experience with version control using Git, preferred.

Interested in this position?

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