Lead Data Scientist (AI/ML)

GatherUp•Walnut Creek, CA

1d•$140,000 - $180,000•Hybrid

About The Position

Customers don't window shop anymore. They search, compare, and decide online. GatherUp helps elevate honest businesses in local search, ensuring these businesses show up, stand out, and win by strengthening their online presence leveraging reviews and customer experience feedback. Our AI-powered platform transforms customer signals into trust, visibility, and growth. GatherUp is owned by Insight Integrity, a holding company focused on trust technology and digital integrity. Its portfolio includes The Transparency Company, an AI-powered review verification and protection platform, and GatherUp. Mission As Lead Data Scientist at GatherUp, you’ll own the design and development of AI/ML models that help shape the integrity of online commerce for local businesses. This is a high-impact, hands-on role at the intersection of NLP, machine learning, and generative AI. You’ll partner closely with engineering, product, and business stakeholders to build systems that help accomplish our mission, vision and business objectives.

Requirements

3+ years of experience in data science, machine learning, or a related field
Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre-training vs post-training concepts
Proven track record of building and deploying ML models in production environments
Strong experience with NLP and unstructured text data
Proficiency in Python and SQL
Experience training NLP models using ML frameworks and architectures such as PyTorch and RoBERTa
Experience fine-tuning LLMs for production use cases
Experience building and deploying RAG pipelines
Ability to communicate complex model behavior to non-technical stakeholders
Strong ownership mindset — you drive projects end-to-end and hold yourself accountable to outcomes

Nice To Haves

Master's degree in a quantitative discipline (e.g. Data Science, Computer Science, Statistics, Engineering, or related)
Experience in and passion for fraud detection, trust & safety, or review/content integrity

Responsibilities

Build AI/ML solutions end-to-end: design, data preparation, feature engineering, model selection, finetuning, training, deploying, validation/testing, and performance analysis
Ensure models are scalable, monitored, and continuously improved in production
Create reproducible training and evaluation pipelines (versioning, experiment tracking, robust validation, clear documentation).
Use behavioral, textual, and statistical signals to identify, monitor and detect anomalies and emerging patterns in data
Apply NLP techniques to analyze unstructured text and surface patterns at scale
Conduct exploratory research and data analysis to identify trends
Partner with engineering, product, and business teams to translate requirements into product
Communicate model behavior, trade-offs, and impact clearly to both technical and non-technical audiences