9 Survival Analysis Jobs

Qualification Masters related to Bioinformatics and Computational Biology Role & responsibilities - Combine and analyze multi-omics datasets to find common biological signals and actionable targets. - Classify disease and immune subtypes from both bulk and single-cell data using supervised and unsupervised machine learning methods. - Organize public datasets, evaluate analytical tools, and standardize workflows for clarity and reuse. - Conduct quality control, normalization, subtype and signature predictions across various sequencing platforms. - Create and maintain complete analysis pipelines for new technologies such as spatial transcriptomics - Search large consortia or databases for comparative studies and hypothesis generation. - Optimize resource use and job scheduling on Linux or HPC clusters; maintain version control and documentation. Preferred candidate profile - Programming & Scripting: R, Python, UNIX shell - Statistics & ML: Feature selection, clustering, predictive modeling, dimensionality reduction, survival analysis - Bulk & Single-Cell Analytics: RNA-seq, WES/WGS, methylation, proteomics, RPPA, scRNA-seq - Workflow & Reproducibility: Workflow managers, such as Nextflow or Snakemake, containers, Git - Data Resources: Major public repositories like TCGA and GEO, and internal cohort data management

JOB SPECIFICATIONS: Bachelor's or Masters degree in relevant discipline. Minimum of 3 years’ experience in this position. Patience, understanding, and willingness to help. Proficient in Microsoft Applications, Good technical skills. Should be good in Communication, Email and Telephone etiquette. JOB DESCRIPTION: To collect, interpret and analyse the data related to hospital from all the department. To compile and analyse the data related to DNB courses conducted in the hospital. To coordinate with all departments staffs and validating the data concerning to the DNB courses To calculate sample size requirements for clinical studies. To provide statistical expertise and contributions for analyzing the data of research projects conducted by DNB pursuing doctors. To provide statistical support for the projects/studies/audits conducted by the doctors. To actively participate in scientific research committee in reviewing of research protocols and providing statistical input To provide statistical support and analyze data related to the audits conducted by the departments in the hospitals. To monitor and validate the data and providing statistical input into other discipline activities and participate in interdepartmental processes. To conduct biostatistics classes for the M.Sc. students studying in allied health science To invigilate examinations conducted by the university. To assess the performance of the students with periodic test and educational activities. To engage the students in curricular activities. Actively participate in Staff training activities. To contribute to professional conferences and Seminars in your field of expertise. To support the MRD department in collection and maintaining the data from all the departments Any other jobs assigned by the management in maintaining and improving the quality of the data. Should report to the Advisor, the Principal, and the Head of the Department.

The Economic Analyst, North America (NAM) position at Mastercard Economics Institute (MEI) involves engaging in data analytics and economic research for the U.S. and Canada. Reporting to the VP, Lead Economist for North America at MEI, you will be responsible for supporting client and stakeholder engagements, collaborating with external clients and partners, and generating initial insights to create impactful storylines and visuals. You will also be involved in synthesizing analyses into clear recommendations, writing reports and client presentations, enhancing existing products, and proactively seeking new knowledge to improve productivity. The role requires a Bachelor's degree in Economics, Statistics, or Mathematics, with experience in statistical modeling, quantitative analysis, and R development, focusing on economic research. Proficiency in SQL and Hadoop is essential, along with expertise in R, Python, or other statistical packages. Experience with Tableau is preferred, and knowledge of JavaScript for data visualization is a plus. Familiarity with econometric and statistical techniques such as predictive modeling, regression analysis, time series modeling, and data mining methods is necessary. A willingness to learn additional statistical applications and software is expected. Candidates with prior experience in the financial services industry will be given preference. Strong communication and writing skills are essential for this role, along with the ability to actively participate in thought leadership activities and contribute to the continuous improvement of quality and productivity within the organization.,

As an Economic Analyst for North America (NAM) at the Mastercard Economics Institute (MEI), you will play a crucial role in contributing to economic research and data analytics for the U.S. and Canada. Reporting directly to the VP, Lead Economist for North America, you will be responsible for engaging in client and stakeholder interactions, collaborating with external partners, and generating actionable insights to support impactful economic storylines and visuals. Your role will involve synthesizing analyses into clear recommendations, assisting in the creation of reports and client presentations, and enhancing existing products while also contributing to the development of new solutions. You will be expected to proactively seek new knowledge, structure project work efficiently, and actively participate in thought leadership activities to continuously improve the quality and productivity of economic research initiatives. To excel in this role, you must hold a Bachelor's degree in Economics, Statistics, or Mathematics, with a strong background in statistical modeling, quantitative analysis, and data engineering, particularly in economic research. Proficiency in SQL and Hadoop is essential, along with expertise in statistical packages such as R, Python, and Tableau. Knowledge of JavaScript for data visualization is advantageous, and experience in financial services would be beneficial. In addition to technical skills, excellent communication and strong writing abilities are required for effective collaboration and presentation of insights. You should be willing to learn new statistical applications or software as needed and demonstrate proficiency in key econometric and statistical techniques to support the Institute's mission to provide valuable economic insights for customers, partners, and policymakers.,

Role & responsibilities: : Provides support across all assigned statistical tasks during the lifecycle of the project, from protocol to CSR. Prepares Statistical Analysis Plans (SAPs), including development of well-presented mock-up displays for tables, listings, and figures. Collaborate with the sponsor, if required. May be responsible for the statistical aspects of the protocol, generation of randomization schedule, publications and input to the clinical study report. Coordinates the activities of other biostatistics and statistical programming personnel on assigned projects to ensure timely completion of high quality work. Provides independent review of project work produced by other biostatisticians in the department. Creates or reviews programming specifications for analysis datasets, tables, listings, and figures. Reviews SAS annotated case report forms (CRFs), database design, and other study documentation to ensure protocol criteria are met and all data is captured as required to support a high quality database and the planned analysis. Conducts and participates in verification and quality control of project deliverables, ensuring that output meets expectations and is consistent with analysis described in SAP and specifications. Implements company objectives, and create alternative solutions to address business and operational challenges. Serves as biostatistics representative on project teams, interfacing as necessary with other departmental project team representatives. This would include preparing in advance for internal meetings, contributing ideas, and demonstrating respect for opinions of others. Manages scheduling and time constraints across multiple projects, sets goals based on priorities from management, adapts to timeline or priority changes by reorganizing daily workload, and proactively communicates to biostatistics management any difficulties with meeting these timelines. Monitors progress on study activities against agreed upon milestones and ensures the study timelines for project deliverables are met. Identifies out of scope tasks and escalate to management. Provides statistical programming support as needed. May participate in Data Safety Monitoring Board and/or Data Monitoring Committee activities, including charter development and serving as an independent non-voting biostatistician. May lead projects involving integrated analyses, attend regulatory agency meetings or respond to questions, as needed, to support the statistical analysis results of clinical trials on behalf of the sponsor. Follows applicable SOPs, WIs, and relevant regulatory guidelines (e.g. ICH). Maintains well organized, complete, and up-to-date project documentation, and verification/quality control documents and programs; ensuring inspection readiness. Displays willingness to work with others and assists with projects and initiatives as necessary to meet the needs of the business. Supports business development activities by contributing to proposals, budgets, and attending sponsor bid defense meetings. Coaches and mentors other Biostatistics staff. Performs other work-related duties as assigned. Minimal travel may be required. Qualifications Graduate degree in biostatistics or related discipline. Moderate experience in clinical trials or an equivalent combination of education and experience. Proficiency in programming. Ability to apply knowledge of statistical design, analysis, relevant regulatory guidelines, and programming techniques utilized in clinical research and to effectively communicate statistical concepts. Experience across all statistical tasks required to support clinical trials during the lifecycle of the project, from protocol to CSR. Excellent written and verbal communication skills. Ability to read, write, speak, and understand Englis

We are looking for an experienced Data Scientist to work at one of our global biopharma customers on a range of Biostats models consulting and development engagements. They are expected to bring extensive knowledge in best practices on R package development, model development and deployment on Databricks, collaboration with version control systems, and familiarity with other topics such as data architecture and cloud infrastructure. Desired Skills and experience Candidates should have a B.E./B.Tech/MCA/MBA in Finance, Information Systems, Computer Science or a related field Strong experience in R programming and package development Proficiency with GitHub and unit testing frameworks. Strong documentation and communication skills. A background or work experience in biostatistics or a similar discipline (Preferred). Expert knowledge in Survival Analysis (Preferred) Statistical model deployment, and end-to-end MLOps is nice to have. Having worked extensively on cloud infrastructure, preferably Databricks and Azure. Shiny development is nice to have. Can work with customer stakeholders to understand business processes and workflows and can design solutions to optimize processes via streamlining and automation. DevOps experience and familiarity with software release process. Familiar with agile delivery methods. Excellent communication skills, both written and verbal Extremely strong organizational and analytical skills with strong attention to detail Strong track record of excellent results delivered to internal and external clients Able to work independently without the needs for close supervision and also collaboratively as part of cross-team efforts Experience with delivering projects within an agile environment Key responsibilities include: Evaluate and document R packages, including metadata and user-focused use cases. Develop unit tests aligned with best practices in R package development. Collaborate closely with internal stakeholders. Design and implement technical solutions for Survival Analysis, based on statistical and business requirements Develop professional quality R packages. Provide consultancy on Biostats model development and deployment best practices. Review and optimize code, integrate existing modelling code into packages. Design and implement end to end modelling and deployment process on Databricks. Support and collaborate with adjacent teams (e.g. products, IT) to integrate the modelling solution. Continually innovate with the team and the customer on using modern tooling to improve model development and deployment. Demonstrate high attention to detail, should work in a dynamic environment whilst maintaining high quality standards, a natural aptitude to develop good internal working relationships and a flexible work ethic Responsible for Quality Checks and adhering to the agreed Service Level Agreement (SLA) / Turn Around Time (TAT)

Job Title: Data Scientist Location: Bangalore, India Experience: 3+ Years Role & Responsibilities: We are looking for a highly motivated Data Scientist to join our analytics team in Bangalore. This role is ideal for individuals who possess strong machine learning and data engineering skills and are eager to solve complex problems in the financial technology space. You will work on developing predictive models, building scalable data solutions, and contributing to key decision-making processes. Design, build, and validate machine learning models including Logistic Regression, Random Forests, GBM, and Survival Models. Perform rigorous model evaluation using techniques such as K-Fold Cross Validation, Out-of-Time (OOT) validation, and X-Tab analysis. Utilize Python (via PyCharm/Jupiter), scikit-learn, PyTorch or TensorFlow for end-to-end model development. Analyse large datasets using SQL and Excel to derive actionable insights. Develop and deploy APIs to serve machine learning models in production environments. Apply statistical techniques such as mean/variance analysis, probability distributions, and simulations to drive model accuracy and relevance. (Optional) Work with lending-specific metrics such as vintage curves, roll forward tracking, and bounce rates to enhance financial models. Strong ML skills: Logistic, Random Forest, GBM, survival model, K fold test, OOT, X-Tab etc. Experience using scikit-learn, pytorch or tensor flow. Experience: 3+ Years Python and usage of PyCharm/ Jupiter, SQL, Excel. Well versed in API development - Strong mathematical ability. mean, variance, probability distributions, simulation etc. Understanding of lending metrics such as vintage curve, roll forward, bounces etc. (Good to have not mandatory) Engineering background preferred IIT/NIT plus not must. Prior experience in Lending Fintech preferred.

Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills

Job Information Job Opening ID ZR_1640_JOB Date Opened 13/12/2022 Industry Technology Job Type Work Experience 8-12 years Job Title Sr Technical Lead City Hyderabad Province Telangana Country India Postal Code 500001 Number of Positions 4 Roles & Responsibilities: Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2B39C2;border-color:#2B39C2;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> I'm interested