377 Mds Consultant jobs in the United States
Regional MDS Nurse Consultant
Posted today
Job Viewed
Job Description
Job description
We are looking for a friendly, reliable and long-term candidate to provide clinical leadership in the development, implementation, coordination and evaluation of MDS services across multiple facilities. The Regional MDS Nurse Consultant will support quality care and fiscal responsibility through comprehensive MDS training and support services for assigned region. You will be responsible for the training and program review of MDS Services in accordance with Federal, State and Local laws and governing entity regulations.
Regional MDS Nurse Consultant role will cover facilities in Georgia.
Qualifications
- Currently licensed as RN /LPN in the state of Georgia
- Associate or bachelor’s degree from an accredited nursing school required.
- Minimum of five (5) years in long-term care required,
- Minimum of five (5) years working as an MDS Nurse in long-term or acute health care
- At least two (2) years of multi-facility, regional MDS experience preferred.
RESPONSIBILITIES
- Consults with and provides technical assistance to the MDS Coordinators through visits and the interpretation or clarification of policies and regulations.
- Trains new MDS Coordinators in conducting resident assessments, developing plans of care, evaluating residents’ responses to interventions and documenting clinical records.
- Trains new MDS Coordinators on the RAI manual and all applicable deadlines for resident assessments and completion of Minimum Data Sets (MDSs).
- Observes MDS and related practices for compliance with standards and regulations.
- Regularly inspects the facility and nursing practices for compliance with standards of nursing practice and federal, state and local regulations
- May be required to assume the role of interim MDS Coordinator, as needed.
- Ability to train facility MDS regarding company best practices including consistent coordination with other members of Compliance Team i.e. DON, BOM, Medical Records, and Therapy to ensure compliant billing.
- Leads the facility management staff and consultants in developing and working from a business plan that focuses on all aspects of facility operations, including clinical management.
- Responsible for developing and implementing appropriate metrics and benchmarks for company's quality of care, against which performance is evaluated.
- Regularly advises and directs Clinical Support Team, Director of Nursing to maximize resident satisfaction and wellbeing.
- Develops and utilizes a standardized process to evaluate and evolve practice to decrease variability and improve the care and safety of patients.
- Responsible for developing, implementing and monitoring quality management policies and procedures for quality data collection and reporting on QM measures.
- Conduct ongoing assessments of the existing eligibility and referrals, case management, disease management systems, and Quality Management programs within each clinical. Provide objective evaluation and recommendations for those systems.
- Review existing clinic information system capabilities for the tracking and monitoring of quality indicators. Make the necessary adaptations for standardized reporting across all centers
- Resident Assessment Instrument (RAI) guidelines are followed in the assigned region with focus on resident care and mixing financial reimbursement through the MDS process. Responsible for ensuring accurate and timely completion of resident assessments, in accordance with Medicare, Medicaid, OBRA and other payer program requirements.
- Ensure regulatory compliance to all federal, state and local regulations and laws relating to nursing home administration; guide facilities to operate within established company policies and practices
- Ensures each facility maintains building and grounds to appropriate standards and that equipment and work areas are clean, safe and orderly, and any hazardous conditions are addressed; ensure that Universal Precaution and Infection Control, Isolation, Fire Safety and Sanitation practices and procedures are followed.
- Helps the Administrator prepare staff for inspection surveys, instructing staff on matters of conduct and disclosure, being interviewed by inspectors, immediate corrections of problems noted by surveyors, etc. Reviews and reinforces important standards previously cited.
- Participates in the preparation of the Plan of Correction response to an inspection survey and implements any follow up QA required for any nursing allegations.
- Provides 24-hour “on call” service to the nursing center in case of emergency.
- Assures that an adequate orientation and in-service training program is provided for MDS personnel.
- Other duties, responsibilities and activities may change or assigned at any time with or without notice.
EQUAL OPPORTUNITY EMPLOYER
Clinical Data Scientist
Posted today
Job Viewed
Job Description
At Memorial Hermann, we pursue a common goal of delivering high quality, efficient care while creating exceptional experiences for every member of our community. When we say every member of our community, that includes our employees. We know that when our employees feel cared for, heard and valued, they are inspired to create moments that exceed expectations, while prioritizing safety, compassion, personalization and efficiency. If you want to advance your career and contribute to our vision of creating healthier communities, now and for generations to come, we want you to be a part of our team.
Job DescriptionPosition is responsible for analyzing complex and unstructured healthcare data sets using advanced statistical methods for use in data driven decision making. The candidate is responsible for supporting a cross-functional team and providing in-depth data insights for complex healthcare problems that can be approached with advanced analytic techniques. They should also collect, explore, and extract insights from structured and unstructured data for performance and quality improvement in a healthcare setting. The ideal candidate should have experience with the EPIC EMR system. They should also have the ability to write complex SQL queries, design Tableau dashboards, and have knowledge of other visualization platforms such as Microsoft Power BI. Knowledge of healthcare comparative analytics platforms such as Vizient, Leapfrog, or US News and World Report is preferred.
Minimum QualificationsEducation: Masters degree with minimum of five (5) years professional experience is required; Professional experience in medical informatics, healthcare information technology/finance/revenue cycle data management, or EHR data management is preferred; In lieu of Masters degree, 10+ years of relevant professional experience may be substituted
Licenses/Certifications: (None)
Experience / Knowledge / Skills:
- Performs research, analysis, and modeling on organizational data
- Develops and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions. Provides findings and analysis for use in decision making
- Handles moderately complex issues and problems, and refers more complex issues to higher-level staff
- Possesses solid working knowledge of subject matter; May provide leadership, coaching, and/or mentoring to subordinate group
- Strong programming skills in addition to working knowledge and experience of statistical analysis tools
- Demonstrated problem solving, analytical reasoning and decision-making skills
- Demonstrates ability to identify and seek needed information to perform problem/situation analysis
- Strong understanding and experience in researching and resolving data issues with a logical, instinctive, and problem-solving mentality working with large, complex and incomplete sources
- Business analytical skills (process flows, procedures, spreadsheets, modeling, etc.), technical expertise, mathematical skills and good understanding of design and architecture principles are required
- Exhibit strong project management skills, with an ability to work independently on multiple projects with competing priorities and a strong commitment to meeting goals and deadlines
- Understanding of database management tools
- Excellent analytical skills and ability to understand and interpret results based on advanced statistical techniques
- Strong written and verbal communication skills in IT and business environments; ability to communicate to technical and non-technical audiences
- Ability to work under minimal supervision in a fast-paced multidisciplinary environment
- Advanced knowledge of health care, health policy, pharmaceutical, medical device, and related issues
- Superior customer service in the form of first-rate work product and project management
- Strong ability to manage challenging client situations
- Strong ability to troubleshoot and recommend solutions
- Strong ability to translate complex information for a wide range of stakeholders
- Effective oral and written communication skills
- Work collaboratively with cross-functional teams to draw insight and intelligence from large datasets and electronic medical records.
- Provide in-depth data insights from structured and unstructured data for complex business problems through use of advanced analytics techniques, predictive modeling, data mining/visualization and pattern analysis tools.
- Lead and manage the data management of CCR-related reporting sources, including data schemas, data architecture, data quality, data security, data governance, data extraction, and loading and transforming from multiple resources.
- Develop and test hypotheses and communicate findings in clear, precise and actionable manner to project and leadership teams.
- Respond to CCR-related data requests and create ad-hoc queries to support projects and planning.
- Work closely with teams to identify, understand, and resolve data issues and improve efficiency, productivity and scalability of data processes.
- Assist with the evaluation of data analytic vendors and tools.
- Ensures safe care to patients, staff and visitors; adheres to all Memorial Hermann policies, procedures, and standards within budgetary specifications including time management, supply management, productivity and quality of service.
- Promotes individual professional growth and development by meeting requirements for mandatory/continuing education and skills competency; supports department-based goals which contribute to the success of the organization; serves as preceptor, mentor and resource to less experienced staff.
- Demonstrates commitment to caring for every member of our community by creating compassionate and personalized experiences. Models Memorial Hermann's service standards by providing safe, caring, personalized and efficient experiences to patients and colleagues.
- Other duties as assigned.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
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Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.
Clinical Data Scientist
Posted 3 days ago
Job Viewed
Job Description
Job DescriptionJob DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next- platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Data Scientist to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for clinical and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature .
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.