Clinical Data Scientist Job Description, Key Duties and Responsibilities

Clinical data analyst job description, duties, tasks, and responsibilities.
Clinical data analysts apply the knowledge of advanced machine learning technologies and statistical analysis uncovering deep insights from data in the healthcare industry.

Clinical Data Scientist Job Description, Key Duties and Responsibilities

If you are searching for the clinical data scientist job description, this post gives you the information you are looking for to learn about what they do.

It presents the key duties, tasks, and responsibilities that typically make up the clinical data scientist work description in most organizations.

It also provides the major requirements most recruiters commonly ask for when hiring for the clinical data scientist position.

Please, continue reading to increase your knowledge of what clinical data scientists do?

What Does a Clinical Data Scientist Do?

Clinical data analysts are responsible for uncovering deep insights from data using advanced machine learning technologies and statistical analysis.

Their job description entails processing very large data sets using cloud-based data pipelines, variety of analytic tools, and visualizations and build predictive models from disparate data sets to uncover patterns in high-density data, and delivering actionable healthcare insights and solutions.

Clinical data scientists work with healthcare organizations, research-based biopharmaceutical company, medical facilities, etc.

They are accountable for working alongside internal colleagues to design and implement data analysis plans, and to summarize the actionable findings to support both exploratory research and new drug application activities.

They also analyze complex clinical data, including but not limited to genomic data, protein assay data, cytokine, and chemokine data from patient samples, and develop novel predictive models using statistical techniques and machine learning to support patient stratification and biomarker selection in clinical trials.

The clinical data scientist work description also involves providing machine learning, predictive modeling, and quantitative data analysis expertise within the organization.

It also includes developing and validating the analysis workflow, software applications, and data warehouse to improve visualization, integration, and accessibility of complex clinical data in the organization.

Clinical Data Scientist Job Description Example/Sample/Template

Clinical data scientists perform various functions, including providing expertise in working with various structured and unstructured healthcare related data sources and undertaking predictive and prescriptive modeling and analysis for various healthcare problems.

The responsibilities of the clinical data scientist may vary depending on the need of the organization they work for, but the primary tasks, duties, and responsibilities that commonly define their job description are listed below:

  • Responsible for the analysis of structured and unstructured clinical records to define phenotypes for genetic association analyses and related activities
  • Translate business problems into precise analytical solutions with measurable business metrics
  • Work together with investigators to establish clinical data workflows for established and emerging studies
  • Translate reputable and in-house developed methods into hardened workflows and systems
  • Utilize software and publications to distribute tools and results
  • Responsible for conveying information on findings and platform requirements with internal and external stakeholders
  • Responsible for constructing end-to-end data science solutions to improve healthcare outcomes and reduce the cost
  • Advance conversational AI solutions to improve healthcare experience
  • Build customer segmentation models to facilitate superior understanding of customers and modify the clinical outcome and healthcare experience for them
  • Responsible for developing scalable and efficient modeling algorithms that can work in production systems
  • Cooperate with the engineering team to build end-to-end cloud based machine learning production pipelines.

Clinical Data Scientist Job Description for Resume

If you have worked before as a clinical data scientist or are presently working in that role, and are making a resume for a new job, you can make the professional experience part of your resume using the duties and responsibilities of the role provided in the sample job description above.

By writing a good professional or work experience, you will be able to effectively show the recruiter that you have been successful performing the duties and responsibilities of a clinical data scientist, which can make your resume more appealing to them.

Clinical Data Scientist Requirements – Skills, Knowledge, and Abilities for Career Success

If you are seeking employment as a clinical data scientist, you may be expected to fulfill the following requirements to convince the recruiter that you can effectively carry out the obligations, purpose, and objectives of a clinical data scientist in their organization:

  • Education: Applicants for the clinical data scientist job are required to have a Master’s or higher degree in Biostatistics, Bioinformatics, or Computer Science, or in a related field
  • Knowledge: it is important that applicants are familiar with clinical data standards (ICD9/10, SNOMED, LOINC, etc.) and their uses in EHR/EMR systems. They should also have adept knowledge of core statistical principles and statistical methods (such as regression modeling, modeling with missing data, and multiple hypothesis testing), and statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets relevant to clinical data
  • It is also vital that they are familiar with statistical software (such as R, pandas, sklearn) and scripting and database languages such as SAS, R, Python, Pipeline Pilot or KNIME, Tableau, or Spotfire, SQL, and other relational databases. Some employers also include a good understanding of Biology, Chemistry, and Drug Discovery as a requirement for employment
  • Communication skills: Applicants need to have exceptional writing and verbal communication abilities to convert analytical methodology/processes into clear terms for internal/external stakeholders, and to present data in an understandable form to a non-technical audience
  • Interpersonal skills: They must be able to interact effectively across different disciplines and with multiple stakeholders, as well as network and source new information or ideas to harness the knowledge within the organization and industry
  • Collaboration skills: Applicants may also be required to collaborate with engineers and other relevant professionals. So it is essential that they are able to work with people of varied background and within functional teams
  • Technical skills: As clinical data scientists, it is important that applicants have a combination of technical skills in the following areas: Big data management tools, Hadoop, NoSQL datastores, as well as more traditional relational databases; Capability in building end-to-end data science solutions, and employing machine learning methods to real world problems with measurable outcomes; deep knowledge of machine learning algorithms, including deep neural networks, natural language, and outlier detection methods; Skillful with data visualization and presentation tools to convert complex analysis into insight, and ability to manipulate and analyzing complex, high-volume, high-dimensionality and unstructured data from multiple sources.

Conclusion

To hire for the clinical data scientist role, recruiters or Hr managers need to publish the job description of the position to help inform interested individuals of the major duties and responsibilities that the candidate that will be hired will be required to perform.

They can apply the clinical data scientist job description example above as a template in making the perfect description of the role for their organizations.

This article is also valuable to individuals who are interested in the clinical data scientist career to learn about the duties associated with the job.