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Applicable languages and platforms include Python, SQL, R, Git for version control, Snowflake, Databricks, and AWS. Entry to mid-level skills in data analytics and management languages such as SQL, Python, or R.
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Develop scientific applications using R, Shiny and/or Python. Knowledge of technology tools and platforms such as MATLAB, R languages, PostgreSQL, GitHub, Linux, Python or Shiny.
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Skills : Java,Advanced Model Architectures,AI Scalability,AI Security and Ethics,attention mechanisms,Continuous Integration/Continuous Deployment (CI/CD),COSMOS DB,Domain Knowledge,FastApi,Gen AI,Leadership,Multimodal AI,Postgres SQL,Python,R Programming,REACT,Research Acumen.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Three years of experience with programming languages, such as Python, C, Ruby, Perl, R, Go, Rust, or similar languages. The Scientific Systems High Performance Computing [HPC] Engineer [SSE] will support the Linux/Unix-based gene sequencing and bioinformatics needs of the National Human Genome Research Institute (NHGRI) within the National Institutes of Health (NIH.
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Proficiency in programming and scripting languages, including Python, R and SQL. Familiarity with medical coding systems (ICD, CPT, HCPCS, NDC, LOINC, SNOMED, etc.) biomedical science, software engineering, and program.
ExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Knowledge of statistical modeling, database management, data visualization, server hardware/software management, web development skills, or algorithm development. Apply knowledge of relational databases (e.g., PostgreSQL) to optimize extraction and analysis of multivariate data Use advanced knowledge and proficiency with a variety of statistical and computational techniques.
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Strong data analysis skills (e.g., SQL, python, R) along with an understanding of technical patterns used to consume and process data at scale (e.g., graphQL, spark) You are also able to coach others and be a mentor in Ontology and Data Modeling.
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Experience with big data analytics, data engineering, data pipelines and experience with LLMs and python scripting and tooling such as databricks. Strong scripting knowledge in R & SQL. Hands on programming experience in R for Data analysis, Statistical inferencing and data science modelling in R.
$119,800 - $263,600 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Highly tuned emotional intelligence, good listener, and deep seated empathy for teams, partners, and direct reports.
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Strong experience with open-source statistical programming tools (Python/R) for analysis and data visualization. Strong experience with open-source statistical programming tools (Python/R) for analysis and data visualization.
$89,000 - $168,000Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Basic programming skills (VBA, Python, R, JavaScript) Familiarity with cloud computing services (Azure, AWS, Google Cloud) Basic programming skills (VBA, Python, R, JavaScript) Business Intelligence Analyst - Specialized Solutions.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Proficiency to manipulate data (Python, R, SQL, SAS) Candidates will be given special consideration for extensive experience with Python. Proficiency to manipulate data (Python, R, SQL, SAS.
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Use data analysis and visualizations (examples include Looker, Jupyter Notebooks, Python, Pandas, and R) to inform the business strategy. Fluent in Python, numpy, scipy, pandas, and sklearn preferred.
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Proficient in the use of computer software, especially packages for statistical analysis (SAS, R, or Python) and knowledge of computing platforms and data file construction. Knowledge of the principles, processes, and methods of social science research and application for quantitative analyses, survey research and/or program evaluation.
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3-5 years of professional experience programming statistical analyses in SPSS, Stata, Python or R (Python and R highly preferred) Build scalable and reproducible work in Python or R including data ingestion, quality checks, cleaning, analysis, modeling, and output.
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