Enterprise Data Scientist: Predictive Analytics & AI

S27a

New York (NY)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

VapTales, a Generative AI platform, is seeking a Data Scientist to join a team solving 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.

Collaborate with stakeholders, design experiments, and communicate findings with clear visuals to guide strategic decisions in a fast-paced

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.

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.

Skills

Python
SQL
Statistics
Data analysis
Communication

Education

Bachelor's or Master's in Data Science/Statistics/Math/CS

Tools

Cloud analytics platforms
NLP familiarity

Job description

VapTales, a Generative AI platform, is seeking a Data Scientist to join a team solving 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.

Collaborate with stakeholders, design experiments, and communicate findings with clear visuals to guide strategic decisions in a fast-paced

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