• Collect, clean, and preprocess large volumes of structured and unstructured data from multiple sources. • Develop and maintain data pipelines to ensure the accurate and efficient processing of data. • Handle data inconsistencies, missing values, and outliers, ensuring high-quality, usable datasets for analysis. • Perform detailed exploratory data analysis (EDA) to understand data patterns, trends, and relationships. • Visualize data using tools such as Tableau or Power BI to identify key insights and drive decision-making. • Apply AI and machine learning algorithms (e.g., classification, regression, clustering, deep learning) to build predictive and prescriptive models. • Train, tune, and evaluate machine learning models to optimize their performance. • Automate model deployment and update processes for continuous improvement in accuracy and efficiency. • Use statistical methods and machine learning techniques to forecast trends, identify anomalies, and detect patterns in large data sets. • Apply natural language processing (NLP) and computer vision techniques for text and image data analysis when needed. • Communicate findings clearly through visualizations and reports to stakeholders across the organization. • Present complex data insights in an accessible and actionable format for both technical and non-technical audiences. • Work closely with cross-functional teams to understand business needs and objectives. • Provide analytical support to business stakeholders by offering data-driven insights and recommendations. • Stay updated on the latest trends in AI/ML technologies and data analytics.

• Analyze integrated and extensive datasets to extract value affecting business decisions • Work collaboratively with key business stakeholders to identify areas of value and deliver insights • Interpret and analyze data from multiple sources including claims, provider, member, and encounters data • Identify and assess business impact of trends • Develop, maintain, and troubleshoot complex scripts and reports using SQL, Excel, or other analytics tools • Contribute to planning and execution of large-scale projects with limited direction • Assist in designing, testing, and implementing process enhancements and opportunities for automation • Identify and perform root-cause analysis of data irregularities and present findings • Manage multiple tasks and data review processes with limited supervision • Demonstrate ownership over projects and understand business value of tasks • Apply expertise in quantitative analysis and data mining to understand customer interaction with analytic products • Communicate findings to non-technical business partners and engage with customers to gather requirements.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a highly motivated Bioinformatics Analyst to join the research group of Dr. Robert Burk at Albert Einstein College of Medicine. This role is central to translating large-scale sequencing datasets into rigorous, publication-ready results with direct relevance to chronic disease, cancer prevention, and infectious disease research. - Pipeline development and leadership: Design, implement, document, and maintain end-to-end NGS pipelines for microbiome and HPV genomics applications. - Large-scale data processing: Perform robust QC, read processing, reference alignment, taxonomic and functional profiling, strain-level analyses, and reproducible reporting for cohort-scale datasets. - Clinical and epidemiologic integration: Harmonize sequencing outputs with clinical and epidemiologic metadata, perform data cleaning and validation, and generate analysis-ready tables. - Statistical and computational analysis: Conduct and interpret statistical analyses using R and/or Python, including microbiome-specific methods and epidemiologic modeling. - Project leadership and communication: Lead defined analysis workstreams, set realistic milestones, communicate risks and dependencies early, and present progress and results in lab meetings and to collaborators. - Troubleshooting and optimization: Diagnose and resolve complex issues, improve robustness, scalability, and runtime efficiency on shared compute environments. - Reproducibility and best practices: Use version control, structured documentation, and reproducible execution practices. - Scientific contribution: Propose fresh analytic ideas, evaluate new tools and methods, and contribute to interpretation and narrative framing of findings. - Manuscripts and grants: Contribute figures, methods text, and analyses for manuscripts and grant applications. Qualifications - Bachelor’s degree in bioinformatics, computational biology, biostatistics, epidemiology, computer science, or a related field; Master’s or PhD preferred. - Strong programming ability in R and/or Python, plus comfort working in a Unix/Linux environment. - Demonstrated experience processing and analyzing NGS data, including building or extending pipelines. - Solid understanding of basic statistical concepts and the ability to translate scientific questions into appropriate analyses. - Track record of independent problem solving, attention to detail, and producing reliable, well-documented outputs. - Strong communication skills and a collaborative mindset for working with interdisciplinary teams. Requirements - Experience in microbiome bioinformatics and/or viral genomics with familiarity with phylogenetics. - Experience working with protected clinical or epidemiologic data and with best practices for data security and governance. - Experience analyzing large cohorts and handling confounding, batch effects, and complex study designs. - Comfort translating analyses into clear figures, methods, and results text suitable for high-impact manuscripts. - Practical experience with bioinformatics work and a proactive attitude towards learning and applying new methods and technologies. Benefits - In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is listed below. - Maximum Salary Range: USD $65,000.00/Yr.

• Collaborate with SMEs across the organisation to define and implement data governance strategies to ensure that master data is consistent, secure and accurate globally. • Play a key role in defining requirements, design, testing and implementation of new processes and system enhancements to support master data. • Assist in leading process standardisation, data governance, cleansing, maintenance and quality improvement efforts in line with data strategy goals. • Conduct root cause analysis on master data inconsistencies/errors and drive corrective actions. • Conduct regular audits of data against established rule sets to ensure consistency and accuracy of information, collaborating with suppliers and business partners to address any data discrepancies. • Provide day-to-day support of the master data governance process to the business user community. • Identify and document existing processes, workflows, gaps, and risks; summarise insights and communicate implications for internal and external stakeholders. • Serve as the vital link between business, the MDM centres of excellence and IT while providing knowledge and advice in own areas of expertise. • Supports the process of identifying, describing, and realising opportunities for the development and use of global master data across information systems. • Support system development activities by assisting in requirements gathering, the drafting of test scripts, test execution, etc.