Early-career role focused on hands-on technical work across client delivery, applied R&D, and internal capability-building in data engineering, machine learning, and AI-enabled workflows.
Compensation
anticipated base salary range for this position in San Francisco, CA is $100,000 - $126,000 annually
Responsibilities
Prepare, inspect, clean, reconstruct, and validate data from a wide range of sources including structured datasets, documents, reports, exports, PDFs, and scans
Use Python, SQL, notebooks, version control, and related tools to build reproducible workflows, test assumptions, troubleshoot issues, and document work performed
Identify data limitations, quality issues, assumptions, blockers, and open questions early
Support applied analytics, machine learning, and AI-enabled workflows
Contribute to workflows involving text extraction, classification, summarization, embeddings, retrieval-augmented generation, model evaluation, automation, visualization, or rapid prototyping
A forward-deployed, hands-on technical expert dedicated to a strategic, US-based pharmaceutical customer, cocreating innovative analytics, AI-driven, agent-based, and data-centric solutions on top of SAS technology.
Locations (2)
New Jersey, New Jersey, United States
United States
Compensation
The base salary range for this position is $136,948 USD - $167,380 USD per year
Responsibilities
Serve as a forward-deployed, customer-embedded consultant working directly with business and technical teams within large pharmaceutical organizations.
Lead time-boxed innovation sprints (typically ~12 weeks) to design and deliver analytics- and AI-enabled capabilities.
Translate real-world business challenges into production-ready solutions built on SAS platforms and integrated into customer systems and workflows.
Apply life sciences and pharmaceutical expertise to identify and solve problems across R&D, clinical development, manufacturing, quality, supply chain, and commercial operations.
The Sr Data Scientist will work in a cross functional team to independently develop and implement Artificial Intelligence based solutions across various disciplines in GE Aerospace, with minimal guidance from senior team members, to deliver business outcomes.
Responsibilities
Understand business problems & processes and develop & implement data science models, including artificial intelligence and machine learning.
Work alongside data scientists, data engineers, software developers, program managers, product owners, and functional stakeholders to translate algorithms into viable products and services.
Work in technical teams in development, deployment, and application of artificial intelligence, machine learning, applied analytics, predictive analytics, and prescriptive analytics ensuring data quality and integrity throughout the data pipeline.
Perform exploratory and targeted data analysis using descriptive statistics and other methods (including collecting, preprocessing, and analyzing large datasets to be used for training and testing machine learning models).
Understand various business & functional processes pertaining to Analytics Development Process.
An 18-month Level 4 Data Analyst Apprenticeship focused on learning how to manage large datasets, spot patterns, and turn data into insights using SQL, Python, and AI.
Compensation
£27,400
Responsibilities
Learn to use SQL and advanced data joins
Perform predictive modelling & forecasting
Data visualization & storytelling
Manage analytics lifecycles & data democratisation
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