Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Statistician Data Analyst And Programmer

PriceSenz
Rock
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Head of Data Science

Data Scientist Genomic Epidemiology - Pathogen

Data Scientist Genomic Epidemiology - Pathogena

Head of Data Science

Baseball Analyst/Data Scientist

Title : Statistician Data AnalystAnd Programmer

Location: Rockville MD 20818

Overall Position Summary andObjectives

Under this task order thecontractor will independently provide epidemiologic and statisticalservices to satisfy the overall operational objectives of the NIMHDDivision of Intramural Research. The primary objective is toprovide services and deliverables through the performance ofsupport services. We are seeking one fulltime statistician/dataanalyst/programmer to support the research activities of the NIMHDDivision of Intramural Research.

MinEducationMasters

Certifications & Licenses

  • Doctorate degree in Biostatistics epidemiologystatistics or a closely related field
  • Applicants with publications in peer reviewed Journalsare preferable
  • Preferred candidates withHealth Disparities research experience

Skills

  1. Scientific Data analysis
  2. Statisticalmodelling
  3. Algorithm development
  4. Data visualization
  5. Machinelearning
  6. Proficiency in using advancedstatistical methods
  7. Linear and nonlinearregression
  8. Expertise to perform the duties ofthe position which include working with NIMHD DIR investigators andfellows to perform data management and data analysis for bothprimary data collection studies and secondary/publicly availabledatasets in a timely manner
  9. Experienceconducting statistical analyses in complex survey data or othersecondary data sources that involve sampling weights (e.g. NHANESNational Health Interview Survey NHIS Medical Expenditure PanelSurvey MEPS)
  10. Experience with structuralequation modelling including but not limited mediation analysiseffect measure modification moderated mediation analysis latentclass analysis (LCA) principal components analysis (PCA) and otherdimensionality reduction methods (structural equation modelling);non parametric statistical methods; quasiexperimental statisticalanalyses (e.g. differenceindifference)
  11. Analyzestudies using highdimensional longitudinal clustered multilevel andrepeated measures data
  12. Familiarity withBayesian statistics and simulation modelling
  13. Experience in working with students or trainees inteaching data analytic skills
  14. Clean condensemerge and reformat data into files that are appropriate for dataanalysis and data sharing including preparing deidentified datasetsand documentation for external users
  15. Createvariables as needed for analyses and document methods anddefinitions for all variables created (e.g. datadictionary)
  16. Expertise in performingstatistical analyses using multiple statistical analysis softwarepackages
  17. Excellent analytical organizationaland timemanagement skills A drive to learn and master newtechnologies statistical methods and techniques
  18. Experience conducting statistical analyses in electronichealth records (EHR/EMR) and administrative claims
  19. Data cleaning
  20. Dataanalysis
  21. Epidemiology
  22. Data mining

Software

  • MPlus
  • SUDAAN
  • ArcGIS
  • R
  • SPSS
  • Python
  • SAS
  • STATA
  • C

Field ofStudy

  • Statistics andDecision Science
  • Computer Programming and DataProcessing
  • Applied Mathematics
  • Management Information Systems and Statistics
  • Mathematics and Computer Science

Statement of Work Details

Performs experimental investigations and similarresearch projects utilizing extensive applications of mathematicaland statistical methodologies.

  • Perform statistical analysis using novel methods andalgorithms.
  • Assist researchers with theplanning implementing and analysis of research projects.
  • Perform data analysis including model building analysisassessing trends determining correlations testing for heterogeneityand compiling and communicating results to investigators toparticipate in the interpretation of results and planning offurther analyses.
  • Provide statistical adviceand consultation to the investigators in study design datamanagement choice and application of statistical methods dataanalysis and interpretation of statistical results.
  • Carry out statistical analyses on issues via descriptiveanalyses causal inference predictive modelling and other univariateand bivariate and multivariate analytic methods.
  • Perform advanced epidemiologic and statistical analysessuitable for studies of health disparities and minority healthincluding (but not limited to): linear and nonlinear regressionmodelling; survival analysis; time series analysis; propensityscore matching weighting standardization multiple imputationmissing data weighting censor weighting and small area estimationto account for confounding missing data loss to follow up selectionbias and other forms of potential bias in studies
  • Conduct statistical analyses; perform data cleaning andformatting data harmonization and data analyses; and prepareresults for publication from intervention studies observationalstudies and secondary data analysis projects using complex surveydata hospital/medical records administrative data or other datasources
  • Advanced epidemiologic and statisticalmethods suitable for studies of health disparities and minorityhealth including (but not limited to): linear and nonlinearregression modelling; survival analysis; time series analysis;propensity score matching weighting standardization multipleimputation missing data weighting censor weighting and small areaestimation to account for confounding missing data loss to followup selection bias and other forms of potential bias instudies
  • Design and conduct statisticalanalyses using complex survey data or other secondary data sourcesthat involve sampling weights (e.g. NHANES BRFSS National HealthInterview Survey NHIS Medical Expenditure Panel Survey MEPS CurrentPopulation Survey and various supplements)
  • Meet with data customers inside and outside the DIR toassess dataset requirements.
  • Performstatistical analyses of large complex datasets preferably using SASfor population health research using existing NIH and publiclyavailable datasets or data collected by NIMHDinvestigators.

Developsoriginal computer code and programs for the application of newmathematical and statistical theories for the solution of proposedproblems related to various scientific studies.

  • Perform data programming analysis andpresentation by preparing charts tables and graphs using softwaresuch as R SAS and STATA.
  • Ensure that all dataproducts (dynamic reports tables and graphics) are reproduciblefrom the original source data by maintaining clear commented andconsistent code and organization of files and folders.
  • Create interim dynamic reports that weave together textcode output tables and graphics and document all procedures andcode used for data cleaning and analysis.
  • Develop and systematically apply data classificationschemes and process and combine data sets for analysis from diversesources.
  • Design and conduct statisticalanalyses using hospital/medical records administrative data andother primary and secondary data sources
  • Design and analyze studies using highdimensionallongitudinal clustered multilevel and repeated measuresdata
  • Design and conduct statistical analysesusing complex survey data or other secondary data sources thatinvolve sampling weights (e.g. NHANES BRFSS National HealthInterview Survey NHIS Medical Expenditure Panel Survey MEPS CurrentPopulation Survey and various supplements).
  • Develop and implement methods and procedures for thecollection processing compilation cleaning and analysis of data incollaboration with DIR investigators and trainees.

Utilizes statistical softwarepackages to manage maintain and analyze large complex statisticaldatabases.

  • Researchmethods in data analysis revise study forms graphically displayanalytic results collaborate in writing or editing drafts ofmanuscripts for publication.
  • Provide acrosstabulation descriptive analysis using standard statisticalprocedures rate standardization stratification of data and modelbuilding.
  • Recommend appropriate statisticaltechniques for analysis of research data and prepare statisticalreports analyze data and use statistical software packages andprograms such as SAS and R.
  • Implement andvalidate cuttingedge algorithms and new statistical methodologiesto analyze diverse sources of data to answer researchquestions.
  • Conduct statistical analyses;perform data cleaning and formatting data harmonization and dataanalyses; and prepare results for publication from interventionstudies observational studies and secondary data analysis projectsusing complex survey data hospital/medical records administrativedata or other data sources.
  • Generate tablesand graphics for abstracts manuscripts and presentations
  • Prepare for publication results from clinical trialsintervention studies observational studies and secondary dataanalysis projects using complex survey data hospital/medicalrecords administrative data or other data sources.
  • Interpret and communicate results of analyses in writtenand oral formats.

Entersand verifies data fields and data dictionaries.

  • Ensure that appropriate variables are capturedin the constructed databases.
  • Format databasesto allow merging of spreadsheets for statistical analyses and tooptimize planned analyses
  • Record Data into aformat appropriate for processing.
  • Applystatistical techniques to produce meaningful tables and graphsusing appropriate software
  • Provide supportwith data sharing including public repositories.
  • Work with staff to prepare and standardize data for thedatabase.
  • Perform routine and general datamanagement.
  • Prepare tables and figures fromdata analyses.
  • Perform database searches andassemble datasets.
  • Analyze studies usinghighdimensional longitudinal clustered multilevel and repeatedmeasures data.
  • Clean condense merge andreformat data into files that are appropriate for data analysis anddata sharing including preparing deidentified datasets anddocumentation for external users
  • Createvariables as needed for analyses and document methods anddefinitions for all variables created (e.g. datadictionary)
  • Transfer data between softwaredataset creation (merge and concatenation) data cleaning (identifyand correct data entry errors and missing values) and datatransformation (create and categorize variables and imputedata).
  • Check and confirm the accuracy ofcalculations conducted by collaborating programmers analysts andpresenters to guard against mistakes in design conduct orpresentation of risk estimates.
  • Collect andrefine new data and refine existing data sources.
  • Create data entry applications to improve data collectionand management.
  • Enhance data collectionstrategy and procedures for primary and secondary data sourcesincluding recovered data sources such as scans and microfilms ofpaper archives.
  • Conduct data collection/entrymanagement cleaning and manipulation activities.
  • Creates Data Workflow Processes.

Collects and analyzes mathematical data andperforms descriptive and missing data analyses.

  • Perform data analysis of data sets involvingstatistical procedures varying in complexity from simple bivariatetests to advanced regression methods for longitudinal data analysisand timetoevent analysis; determine correlations betweenvariables.
  • Perform data analysis includingcrosstabulation descriptive analysis using standard statisticalprocedures as well as model building (logistic regressionconditional logistic regression).
  • Assist staffin conducting evaluations and analyses of programs usingappropriate methods and tools and perform data management and carryout statistical analysis for assigned research projects.
  • Process and analyze data using blindsource separationtechniques.
  • Organize manage and design datafiles and plans for associated statistical analysis.

Tracks and documents allmodifications errors and changes to all databases anddecisions.

  • Prepare and/orupdate data tables and figures methods sections of manuscriptsreports and other documents for presentation and/or publication.
  • Take lead of the storage tracking internalreview and retrieval of information documentation and datasets forall assigned projects and projects of any subordinates.
  • Perform data cleaning formatting variable recoding dataharmonization and data quality checks and data management andmanipulation
  • Transfer data between softwareand create datasets (merge and/or concatenation) data cleaning(identify and correct data entry errors and missing values) anddata transformation (create and categorize variables and imputedata).
  • Review literature and createbibliographies research methods in data analysis revise study formsgraphically display analytic results and collaborate with staff onwriting and editing drafts of manuscripts forpublication

Develops andcoordinates the training program for staff in statistical andmathematical analysis.

  • Attend all lab meetings lab checkins and otherresearchrelated meetings as requested by investigators ortrainees.
  • Report either verbally and/or inwriting regular updates on the progress of their work toinvestigators.
  • Provide expertise onepidemiologic and statistical research methods as needed forresearch projects protocols and proposals
  • Train trainees on developing statistical analytic codesto analyze quantitative data to achieve research objectives andinterpreting results from different statistical analyses
  • Provide periodic training on contemporary epidemiologicand biostatistics analytics approaches to the NIMHD DIR.
IF YOU ARE INTERESTED AND MET THESEQUALIFICATIONS PLEASE APPLY WITH YOUR UPDATEDRESUME!!!

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.

Why the UK Could Be the World’s Next AI Jobs Hub

Artificial Intelligence (AI) has rapidly moved from research labs into boardrooms, classrooms, hospitals, and homes. It is already reshaping economies and transforming industries at a scale comparable to the industrial revolution or the rise of the internet. Around the world, countries are competing fiercely to lead in AI innovation and reap its economic, social, and strategic benefits. The United Kingdom is uniquely positioned in this race. With a rich heritage in computing, world-class universities, forward-thinking government policy, and a growing ecosystem of startups and enterprises, the UK has many of the elements needed to become the world’s next AI hub. Yet competition is intense, particularly from the United States and China. Success will depend on how effectively the UK can scale its strengths, close its gaps, and seize opportunities in the years ahead. This article explores why the UK could be the world’s next global hub for artificial intelligence, what challenges it must overcome, and what this means for businesses, researchers, and job seekers.