Data Scientist - Fulltime

Work Mode : Remote / Potential hire can work from Connecticut / Texas or from Pittsburgh
Pay Range :$90K-$120K /Yr Base + Annual Bonus

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidates skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. We are hiring a Principal Data Scientist to be our most senior technical voice in data science. You will turn business problems into practical machine learning and GenAI solutions, then make sure the wider team can build, deploy and maintain them.
Translate ambiguous business problems into well-scoped data science solutions with clear success metrics.
Design end-to-end solutions, from data requirements and modeling approach to deployment and monitoring.
Build reference implementations, reusable components and templates the team can extend.
Write clear design documents, runbooks and code standards so solutions can be built and supported by others.
set the bar for quality and reproducibility.
Mentor data scientists and ML engineers, and run knowledge-sharing sessions.
Onshore/offshore collaboration

Work with onshore and offshore teams as one unit, with shared standards, tooling and ways of working.
Run design reviews and planning sessions that suit multiple time zones, with clear written decisions.
Keep context flowing between business stakeholders and offshore delivery teams.
Advanced analytics, ML and GenAI

Apply statistical modeling, machine learning and forecasting to problems such as prediction, optimization and segmentation.
Identify and prototype GenAI use cases (for example summarization, document extraction, natural-language data access) and take proven ones to production.
Governance and stakeholder partnership

Advise senior leaders on what data science can and cannot deliver, in plain language.
Work with data engineering and platform teams on pipelines, MLOps and model monitoring.
Uphold responsible-AI, privacy and security standards across all solutions.
Bachelors or Masters in Data Science, Statistics, Computer Science, Mathematics or a related quantitative field (or a bachelors with equivalent experience).
~9+ years in data science or applied machine learning, with a record of solutions running in production.
~ Strong Python and SQL; Deep knowledge of statistics, experimental design and core ML techniques (supervised, unsupervised, time series, NLP).
~ Proven experience designing solutions that other teams implemented and maintained, with documented patterns and handoff.
~ Experience leading or mentoring data scientists and engineers, formally or as a technical lead.
~ Hands-on experience with LLMs: prompt design, retrieval-augmented generation (RAG), fine-tuning and evaluating output quality.
MLOps experience: model versioning, CI/CD for ML, monitoring and retraining (for example MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI).
Experience with cloud data platforms such as Snowflake, Databricks, BigQuery or Microsoft Fabric.
Relevant cloud or ML certifications.