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Lead Data Scientist

Pay
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Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting
Employment
Not stated

What you’ll work on

Full posting
  • Find sources of customer friction in large text datasets using NLP and LLM methods

  • Build measurement systems, ML models and NLP/LLM tools for customer growth and product quality

  • Scope and lead projects with Operations, Engineering, Program and Product Management

  • Guide strategic decisions on customer friction issues using business and data science insight

  • Run technical training and mentor other Data Scientists on the team

From the employer’s posting
pinpoint sources of customer friction buried within massive text datasets
Construct and launch measurement systems, machine learning models, and NLP/LLM tools designed to fuel customer growth and sharpen product quality
Conceive, define scope for, and spearhead impactful projects through tight collaboration with Operations, Engineering, Program Management, and Product Management
Guide strategic thinking and critical decision-making tied to customer friction issues by merging solid business understanding with sophisticated data science approaches
conducting technical training sessions, encouraging ongoing skill development, and guiding other Data Scientists on the team

Tools in this posting

  • Python
  • R
  • SQL
  • Databricks
  • Kafka
  • SageMaker
  • Tableau
  • Matplotlib
  • NumPy
  • pandas
  • scikit-learn
  • Streamlit
Source — Tool mentions in context
Our team is seeking a Lead Data Scientist to join our organization. In this position, you'll apply NLP/LLM techniques alongside broader data science approaches to pinpoint sources of customer friction buried within massive text datasets, while developing tools that speed up friction detection and product enhancement. The ideal candidate brings sharp business judgment, ease operating alongside senior executives, deep statistical knowledge, strong NLP/LLM capabilities, and a track record of working across multiple functional teams Responsibilities Guide strategic thinking and critical decision-making tied to customer friction issues by merging solid business understanding with sophisticated data science approaches Keep pace with the rapidly shifting NLP and LLM field, incorporating cutting-edge research methods into practical business applications Construct and launch measurement systems, machine learning models, and NLP/LLM tools designed to fuel customer growth and sharpen product quality Conceive, define scope for, and spearhead impactful projects through tight collaboration with Operations, Engineering, Program Management, and Product Management Help build a thriving Data Science culture by conducting technical training sessions, encouraging ongoing skill development, and guiding other Data Scientists on the team Requirements A Bachelor's or Master's degree in Statistics, Mathematics, Econometrics, Computer Science, or a closely related area At least 5 years of applicable background in Data Science or comparable fields A minimum of one year spent leading and managing development teams Deep knowledge applying diverse ML approaches, including NLP and LLMs, to address business challenges, paired with sound instincts for selecting the right method for the right problem Background overseeing ML projects in their entirety, spanning deployment through continuous monitoring Advanced SQL skills, complemented by strong capability in another data science language such as Python or R Consistently high standards for deliverable quality, while remaining pragmatic about balancing speed of delivery against future refinement Capacity to break down intricate technical ideas for a range of audiences and build persuasive narratives aimed at non-technical stakeholders Skilled with visualization platforms such as Streamlit, Tableau, or R Shiny, as well as libraries including matplotlib and bokeh Upper-intermediate English language skills or higher (B2) Nice to have Background working with Amazon SageMaker, Apache Kafka, and Databricks to construct and manage machine learning and data pipeline infrastructure Exposure to NLP preprocessing methods used to ready text data for modeling and analysis Strong capability with libraries such as Pandas, NumPy, and Scikit-learn for data handling and model building

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Job description

View original posting ↗

Our team is seeking a Lead Data Scientist to join our organization. In this position, you'll apply NLP/LLM techniques alongside broader data science approaches to pinpoint sources of customer friction buried within massive text datasets, while developing tools that speed up friction detection and product enhancement. The ideal candidate brings sharp business judgment, ease operating alongside senior executives, deep statistical knowledge, strong NLP/LLM capabilities, and a track record of working across multiple functional teams Responsibilities Guide strategic thinking and critical decision-making tied to customer friction issues by merging solid business understanding with sophisticated data science approaches Keep pace with the rapidly shifting NLP and LLM field, incorporating cutting-edge research methods into practical business applications Construct and launch measurement systems, machine learning models, and NLP/LLM tools designed to fuel customer growth and sharpen product quality Conceive, define scope for, and spearhead impactful projects through tight collaboration with Operations, Engineering, Program Management, and Product Management Help build a thriving Data Science culture by conducting technical training sessions, encouraging ongoing skill development, and guiding other Data Scientists on the team Requirements A Bachelor's or Master's degree in Statistics, Mathematics, Econometrics, Computer Science, or a closely related area At least 5 years of applicable background in Data Science or comparable fields A minimum of one year spent leading and managing development teams Deep knowledge applying diverse ML approaches, including NLP and LLMs, to address business challenges, paired with sound instincts for selecting the right method for the right problem Background overseeing ML projects in their entirety, spanning deployment through continuous monitoring Advanced SQL skills, complemented by strong capability in another data science language such as Python or R Consistently high standards for deliverable quality, while remaining pragmatic about balancing speed of delivery against future refinement Capacity to break down intricate technical ideas for a range of audiences and build persuasive narratives aimed at non-technical stakeholders Skilled with visualization platforms such as Streamlit, Tableau, or R Shiny, as well as libraries including matplotlib and bokeh Upper-intermediate English language skills or higher (B2) Nice to have Background working with Amazon SageMaker, Apache Kafka, and Databricks to construct and manage machine learning and data pipeline infrastructure Exposure to NLP preprocessing methods used to ready text data for modeling and analysis Strong capability with libraries such as Pandas, NumPy, and Scikit-learn for data handling and model building
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