Data Scientist – Conversational AI

Jobtailor

Dearborn (MO)

On-site

USD 120,000 - 150,000

Full time

14 days+

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Job summary

Jobtailor is seeking an experienced Senior Data Scientist to drive NLP, ML, and product analytics across multi-source data, including telemetry and user interactions. You will build and evaluate models, define metrics, and enable self-service dashboards with Looker and PowerBI.

Responsibilities include analytics integration in GCP, experiment design with A/B tests, and acting as the bridge between Data Science, Engineering, and Product to transform raw data into actionable business insights

Qualifications

Master's degree in a quantitative, technical, or related field such as Data Science, CS, or Statistics.
7+ years of experience in Data Science, Product Analytics, or Applied ML.
Bridge between Data Science, Engineering, and Product to turn raw telemetry into business insights without a central data team for every step.
Proficiency in Python or R with text analytics, clustering, and categorization; familiarity with LLM evaluation techniques.

Responsibilities

NLP & Utterance Analysis: categorize and cluster raw utterances; perform sentiment analysis on logs to extract insights.
AI Response Evaluation & Experimentation: design methodologies to evaluate AI responses; design and analyze A/B tests for prompts, model updates, and features.
Data Integration & Sanitization: work in GCP to join and structure mobile, customer support, and vehicle data with strict privacy.
Problem Framing & Metric Definition: partner with Product Managers; define core metrics such as task success, engagement, and deflection.
Advanced Visualization & Self-Service: build dashboards in Looker and PowerBI for product team self-service.
Bridge Mobile-to-IVI Gap: standardize mobile data against in-vehicle data contracts as the AI expands.

Skills

Natural Language Processing

Applied Machine Learning

Expert-Level SQL

Python

Data Analytics

A/B Testing

Text Analytics

Clustering

Data Integration

Education

Master's degree in Data Science/CS/Statistics

Tools

Google Cloud Platform

Looker

PowerBI

Git

GitHub

BigQuery

Job description

NLP & Utterance Analysis: Leverage Natural Language Processing (NLP) and machine learning to categorize and cluster raw user utterances. Perform sentiment analysis on unstructured text logs to extract actionable product insights.
AI Response Evaluation & Experimentation: Design methodologies to evaluate the helpfulness, accuracy, and relevance of the AI’s responses. Design and analyze A/B tests to measure the impact of prompt adjustments, model updates, and new feature rollouts.
Data Integration & Sanitization: Dive directly into Google Cloud Platform (GCP) to cleanly join and structure mobile, customer support, and vehicle data into robust "Analytical Sandboxes," ensuring strict adherence to data privacy and PII handling standards.
Problem Framing & Metric Definition: Act as a strategic partner to Product Managers. Challenge assumptions and define core conversational metrics (e.g., task success rates, user engagement, support deflection).
Advanced Visualization & Self-Service: Design, build, and maintain highly intuitive, narrative-driven dashboards using Looker and PowerBI to empower the product team to answer their own day-to-day questions.
Bridge the Mobile-to-IVI Gap: Act as the analytical bridge as our digital assistant expands from the Ford app into the vehicle, standardizing mobile data against our emerging in-vehicle data contracts.

Requirements

Education: A Master's Degree in a quantitative, technical, or related field (e.g., Data Science, Computer Science, Statistics).
Experience: 7+ years of experience in Data Science, Product Analytics, or Applied Machine Learning.
"Full-Stack" Capability: Demonstrated ability to act as a bridge between Data Science, Engineering, and Product—taking raw telemetry, applying statistical/ML models, and transforming it into business insights without relying on a central data team for every step.
Applied ML & LLM Analytics: Proficiency in Python or R with hands‑on experience in text analytics, clustering, and categorization. Familiarity with LLM evaluation techniques (e.g., prompt effectiveness, hallucination tracking, human-in-the-loop feedback).
Expert‑Level SQL & GCP: Highly proficient in writing complex, optimized SQL (Window Functions, CTEs, handling JSON/Nested Data) within Google Cloud Platform (BigQuery) to structure datasets independently.
Advanced Visualization: Deep expertise in building scalable business intelligence solutions, semantic layers, and executive‑facing dashboards in Looker and PowerBI.
Experimentation: Strong grasp of statistics and experience designing and measuring A/B tests in a product environment.
Analytics as Code: Experience with version control (e.g., Git, GitHub) and working in environments where analytics changes go through a formal peer‑review process.
Strategic Problem Solving: Comfortable navigating complex, multi‑source data environments. You view data integration as a puzzle to be solved and a strategic enabler for the business.

Core Competencies

Demonstrates expertise in Natural Language Processing, Applied Machine Learning, and Data Analytics, with a strong focus on building advanced visualizations and conducting A/B testing to drive product insights. Proficient in SQL and Google Cloud Platform, capable of integrating and structuring complex datasets while ensuring data privacy standards.

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