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Data Scientist

Job in New York, New York County, New York, 10261, USA
Listing for: S27a
Full Time position
Listed on 2026-09-12
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Company Overview

Vap Tales is a Generative AI platform focused on agentic orchestration and enterprise-scale workflows. We partner with major global enterprises to curate advanced customer experiences using cutting-edge AI technologies. Building on our success in the retail and e-commerce sector, we are currently expanding our platform to serve the online grocery marketplace. This strategic initiative aims to provide a new, agentic way for enterprise clients to serve online shoppers, integrating advanced AI into high-volume transaction environments.

Job Summary

As a Data Scientist, you will join team that solves complex business problems for enterprise customers through advanced analytics and data-driven decision-making. You will uncover insights, develop predictive models, and help shape strategies that improve customer experiences, operational performance, and business growth.

Key Responsibilities
  • Develop predictive models and advanced analytics solutions.
  • Design experiments and measure business impact through data.
  • Extract insights from structured and unstructured datasets.
  • Partner with business stakeholders to solve complex problems.
  • Communicate findings through visualizations and executive presentations.
Qualifications
  • Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
  • Strong foundation in statistics, machine learning, and data analysis.
  • Proficiency in Python, SQL, and analytical tools.
  • Experience working with large datasets and predictive modeling.
  • Excellent problem-solving and communication skills.
Nice to Have
  • Experience with causal inference and experimentation.
  • Knowledge of cloud-native analytics platforms.
  • Familiarity with NLP, recommendation systems, or forecasting.
  • Experience in enterprise analytics environments.
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