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Job Location | Hyderabad |
Education | B.Tech/B.E. - Any Specialization, B.Sc - Chemistry, Statistics, Physics, B.Pharma - Pharmacy |
Salary | Not Disclosed by Recruiter |
Industry | Pharma, Biotech, Clinical Research |
Functional Area | Medical , Healthcare , R&D , Pharmaceuticals , Biotechnology |
EmploymentType | Full-time |
Position Purpose: Provide excellence in statistical & data managing support to the site and within the sandoz global network to drive the application of advanced and state-of-the-art statistical principles, data aggregation tools and methodologies to improve process understanding, quality and compliance of the products, efficiency and capability of the processes and profitability of the organisation. Major Accountabilities: Product Development and Transfers: Support the development and transfer of oral drug products by evaluation of material, formulation and process parameters by means of applied statistics Lead capture and aggregation of scientific data with the aim to create and maintain database of raw data Utilize DoE concepts and QbD principles to achieve robust formulations and processes Cooperate with the statistical experts of TechOps to enable a smooth process handover Work extensively with formulators both 1:1 and in meetings to work with the DoEs & data models in terms of design, and in interpreting the results Work extensively on desiging mechanistical models of technological processess and IVIVC work hand-in hand with our formulation experts and engineers to enable the successful process transfers to production support the achievement of robust formulations and processes as well as the introduction of quality by designs (QbD) principles Contribute to risk assessments, e.g. FMEA or risk matrix. Planning and evaluation of Design of Experiments (DoEs) in the frame of the Novartis Quality by Design validation strategy. Act as an interface to the formulation team and the IVIVC team (analytical) to assist in the IVIVC modeling, data interpretation, BE assessment etc as per need. Process validation and transfer, in particular Process Analytical Technology (PAT) methods: Support the design of an analytical robustness test, e.g. by means of DoE. Work with analytical team to develop DoEs for optimization of analytical methods Work together with PAT-experts from drug substance and drug product process development to support in DoE, chemometrics and data integrity checks Statistical assessment of method validation data Training & data evaluation: Enable the Site to have the necessary competencies in applied statistical & data handling tools by designing and delivering training on available tools and how to use them in practice, providing ongoing coaching. Provide training in DoE and basic statistical concepts to clients in forms of short courses and/or seminars Instruct how to collect (e.g. sampling plans which are statistically meaningful), set up and interpret data sets and statistical results highlighting constraints and limitations. Support on data mining, trending and other data related activities to get meaningful results. Key Performance Indicator - Successful execution of assigned tasks and work packages Successful interactions in project teams Compliance with Novartis / Sandoz rules and guidelines feedback from leaders / peers .
Keyskills :
process validation data integrity product development data interpretation method validation design validation database maintenance training delivery data mining simca
A global healthcare leader, Novartis has one of the most exciting product pipelines in the industry today. A pipeline of innovative medicines brought to life by diverse, talented and performance driven people. All of which makes us one of the most rewarding employers in our field.
Minimum requirements:Advance degree in statistics/ pharmacy / physics/ chemistry/ engineering or equivalent experience. Fluent in English and proficient in site local language. Proven experience of at least 6 years of applied statistics in the pharmaceutical environment. Experience in design of experiments (DoE) and its analysis is crucial. Familiarity with the statistical aspects of formulation experience in using SAS, JMP or Minitab Experience in data aggregation. Experience in data mining, SIMCA and Monte Carlo simulations are a plus . Experience in the field of drug product development of PAT-tools are a plus. Proven experience of applied statistics is a must, e.g. in the field of DoEs and multivariate data analysis. Experience in the following software is a plus: SAS, R, Minitab, SIMCA-P+, Modde, JMP, SPSS.