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4 Survival Analysis Jobs

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4.0 - 6.0 years

5 - 9 Lacs

Gurugram

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Naukri logo

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)

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3.0 - 8.0 years

5 - 15 Lacs

Bengaluru

Work from Office

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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.

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8.0 - 12.0 years

8 - 12 Lacs

Hyderabad / Secunderabad, Telangana, Telangana, India

On-site

Foundit logo

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

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8.0 - 12.0 years

8 - 12 Lacs

Hyderabad

Work from Office

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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

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