Join the transformative team at City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. City of Hope’s growing national system includes its Los Angeles campus, a network of clinical care locations across Southern California, a new cancer center in Orange County, California, and treatment facilities in Atlanta, Chicago and Phoenix. Our dedicated and compassionate employees are driven by a common mission: To deliver the cures of tomorrow to the people who need them today. ** This is a Fully Remote Opportunity within the United States** As a successful candidate, you will: The Data Scientist will design, develop, and deploy advanced machine learning and artificial intelligence solutions to support cancer research and clinical operations. This role integrates data science, AI engineering, and ML systems development, including deep learning architectures and large language model (LLM) applications such as retrieval-augmented generation (RAG), agent-based systems, and domain-specific model adaptation. The position also involves development of multimodal AI models that integrate structured clinical data, unstructured text, medical imaging, and genomic data. The role requires advanced theoretical and applied knowledge in machine learning, distributed systems, and modern AI frameworks. - Collaborate with administrative leaders, clinicians and IT specialists - Query large datasets from multiple systems - Design, develop, validate, and deploy machine learning and deep learning models, including transformer-based architectures, multimodal neural networks, and large language model (LLM) systems - Architect, deploy, and monitor production-grade AI systems, including LLM-based RAG pipelines, agent frameworks, and multimodal inference systems in cloud or distributed environments. - Produce technical documentation, visualizations and presentations - Lead technical design and implementation of complex AI initiatives involving cross-functional research, clinical, and engineering teams. - Completes own work independently - Design multimodal AI solutions integrating text, imaging, genomic, and structured clinical data using deep learning and transformer-based models. - Performs other related duties as assigned or requested. Your qualifications should include: - Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Applied Mathematics, Bioinformatics, Engineering, or a closely related quantitative field ; or Bachelor’s degree with 3+ years of experience. Preferred: - Familiarity with a health care environment and EHR data - Familiarity with multimodal data such as genomics and medical images - Background in deep neural networks and Natural Language Processing (NLP) - Familiarity with Cloud services platforms like Microsoft Azure - Experience with Generative AI and Large Language Models (LLMs), including RAG, fine-tuning, embedding models, prompt engineering, and integration into agentic data science workflows. - Proficiency with version control systems (Git) and collaborative development workflows - Awareness of the most recent trends and developments in the Data Science / Machine Learning fields Skills: - Experience with relational databases and SQL queries - Proficient in Python and related data and ML packages - Proficient in standard data science workflows, including training, evaluating/testing, and deploying machine learning and deep learning models - Familiarity with LLM frameworks and packages such as LangChain, LangGraph, for building advanced AI solution - Ability to work independently and use creative approaches to problem-solving - Capable of turning questions into testable hypotheses, extracting data from complex databases, creating and evaluating statistical models - Experience in data visualization and ability to communicate results to both technical and non-technical audiences - Experience in authoring and contributing to peer-reviewed scientific publications - Experience in completing end to end projects with minimal to no supervision - Experience in being a part of big projects with many internal and external teams involved - Experience managing collaborative data science projects We currently have 4 Openings City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE.

Role Description Yassir is seeking a highly skilled and motivated Data Scientist to join our Artificial Intelligence (AI) team and contribute to some of our key projects, such as Dynamic Pricing and Trip Dispatching. As a Data Scientist, you will play a crucial role in analyzing and modelling data to optimize our Machine Learning (ML) systems. Your expertise in both predictive modelling and software development will be essential in driving our solutions and providing value to Yassir. This is a very exciting opportunity, tackling some of Yassir’s most critical problems. Key Responsibilities - Become an expert point of contact and thought leader on your scope by mastering the details and principles pertaining to it. - Focus on optimization Pricing capabilities, such as Dynamic / Surge Pricing, Discounts / Commissioning Optimization and Personalized Pricing. - Identify and propose ML opportunities related to your scope and beyond. - Support with requirements definition and prioritization of ML projects. - Collaborate with cross-functional Engineering and Product teams. - Champion Data Quality as a critical input component to all ML solutions and Analytics. - Conduct Exploratory Data Analysis and subsequent Feature Selection / Engineering. - Utilize Statistical and ML techniques, as appropriate, for model training. - Validate and tune ML models. - Visualize analysis / modelling results focusing on meaningful, actionable metrics and insights. - Deploy and test ML applications using our MLOps infrastructure. - Monitor ML models on their technical performance, business impact and underlying data / concept drift. - Explain technical solutions in a business-friendly manner, supporting Product teams in their communications and reporting. - Maintain and improve technical documentation of delivered solutions. - Support the Data & AI domain in developing its technical capabilities, improving its ways of working and collaboration with other dependent teams. - Champion Data Culture, proactively share knowledge across teams, and participate and drive team building activities. Qualifications - Solid Mathematical / Statistical / Machine Learning as well as Software Development technical skills - supported by a Masters degree or above in a relevant quantitative field such as Mathematics, Statistics, Data Science, Machine Learning, Operational Research, Computer Science, Software Engineering, Physics. - Comfortable in efficient, production quality Python and SQL coding at a professional setting with at least 2 years of industry experience. - Comfortable with key software engineering concepts, such as code / memory profiling, code optimization, scalability, code / QA testing, cost optimization and associated best practices. - Prior experience with Pricing / Economics related problems and/or modelling techniques - we welcome Economics / Econometrics backgrounds and experience. - Comfortable with key Statistical concepts, such as statistical testing and causal analysis. - Analytical thinking and problem solving skills. - Engineering mindset focused towards delivering robust applied data science solutions. - Visualization skills, including experience with common Python ecosystem libraries and/or Analytics / BI tooling. - Familiarity and prior use of Cloud solutions and their data / ML services - at Yassir we use Google Cloud Platform (GCP), experience with which is highly preferred. - Mastering of the end-to-end (ML) model development lifecycle. - Excellent communication skills, including presentation and oral / written communication (clear articulation, concise documentation) in professional English. - Positive attitude and resilience. - Strong interpersonal skills focused on peer support, empathy, active listening, team building and stakeholder relationships building. - Internal drive, self-motivation and ability to work independently including own effective project management. Nice to have - Experience with On-demand, Mobility or Financial Services companies. - Experience working on ML features for Digital Products (apps, websites).

• Model development, training pipeline, and analytics backend • Maintain and improve the physics-based simulation engine — 19 equipment families, 64+ fault signatures, first-principles governing equations • Run model training pipelines — dataset generation, feature engineering, model fitting, hyperparameter tuning, MLflow experiment tracking • Implement model retraining triggers — drift detection (PSI-based), accuracy degradation monitoring, scheduled recalibration • Build and maintain the champion/challenger evaluation framework — shadow scoring, A/B testing, promotion guardrails • Develop new fault signatures as customer feedback identifies gaps • Implement probability calibration — Platt scaling, isotonic regression, ECE monitoring • Build the adaptive threshold controller — feedback-driven alarm threshold adjustment based on false alarm rate and recall • Develop the CMMS label linking pipeline — match work orders to predictions with confidence scoring • Analyze prediction outcomes — precision, recall, F1 by equipment family, by fault type, by site • Produce the weekly and monthly accuracy reports • Define and maintain feature sets for each equipment family — physics-informed features, rolling statistics, cross-tag correlations • Monitor data quality metrics — null rates, stale timestamps, schema violations, sensor drift • Build the healthy baseline update pipeline — daily computation of per-tag statistics from healthy operating data • Implement the training data snapshot pipeline — versioned, reproducible dataset extraction with manifest tracking

• Lead large-scale projects from ideation through enterprise impact. • Apply a broad problem-solving toolkit to develop both creative and practical solutions. • Evaluate trade-offs between out-of-the-box and customized solutions, optimizing for speed and effectiveness. • Implement scalable, bug-free, and well-tested solutions that reduce complexity rather than add to it. • Understand business challenges and deliver results that meaningfully solve key problems. • Proactively engage with stakeholders across all levels to align data science efforts with business needs. • Identify and mitigate risks early, preventing roadblocks that could arise later. • Serve as a trusted advisor and thought partner, ensuring projects are delivered on time and aligned with business objectives. • Mentor and collaborate with peers, improving team-wide problem-solving capabilities and technical execution.