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Data ScientistOperations

Arzenovo Pharma Ltd
Freshers
Delhi(Connaught Place ), Faridabad, Gurgaon, Ghaziabad, Noida
5,65,000 - 9,52,000 Per Year
Posted on 23 Apr 19
Job DescriptionLast Date 22 Jun 19
Introduction

    The candidate should have demonstrated experience in data mining methods using large scale data, hypothesis generation, and integration of diverse data sets. The candidate should identify the current gaps in the strategies & methodology and able to come up with improvements in the practiced procedures. 

    Focused on applying data mining techniques, performing statistical analysis, and building high quality prediction systems.
    Help solve manufacturing problems by conducting trend analysis, root cause investigations and process optimization. Bring innovative approach by developing sound hypotheses and proposing a sound design of experiments.
    Collaborate with the R&D and Clinical departments to optimize study designs and critical end points of clinical trials.
    Collaborate to develop an understanding and documentation of business problems, product requirements and success metrics.
    Work as a data strategist and predictive modeler, researching, identifying and integrating data sets and innovative Algorithms.


Responsibilities

    The Data Scientist is an expert position and is instrumental to generate insights using extensive internal and external data with appropriate analysis methods to support the conduct of indication, protocol and site-feasibility assessments. Key tasks includes defining data requirements (e.g. past performance, epidemiology and business/ competitive intelligence databases),conducting searches, consolidating data, leading the analysis, scenario modelling and supports Feasibility Strategists to interpret the results to formulate appropriate recommendations for feasibility.

    • Leads the analysis to generate an initial list of potential investigators and country allocation and site distribution based on past performances, competitive intelligence, availability of patients, incidence and prevalence, standard of care, organisational strategy and other relevant metrics as part of early indication feasibility.


    • Supports the Feasibility Strategist to select countries/sites suitable to conduct protocol and site feasibility.

    • The Data scientist is responsible to maintain and update the Information Hub using varieties of internal and external sources. It covers the following major areas:

    a. Epidemiology, Clinical Practices, Inclusion/Exclusion Criteria, Previous/Ongoing Studies (incl. their performance),Potential Sites/Investigators (incl. experience, performance, warnings etc),Prediction of Study Timeline, covering all legal, regulatory, medical aspects (e.g., disease incidence and prevalence, competitive landscape, standard of care) and operational aspects (logistics, historical performance, and start-up times),Competitor(s),Product pipeline and therapy area assessments, Clinical trial tracking (incl. patient recruitment issues, protocol design issues),Clinical endpoints analysis and Development timelines and other business/ competitive intelligence.

    b. Validation of strategic aspects and operational practicability of the clinical development plan, study concepts and draft protocols, planning and prediction of patient recruitment strategies concerning regions, countries and centres, and predicted enrolment and screening failure rates in close cooperation with the Feasibility Strategist.


    • The Data scientist provides an overview of planned versus actual study/ project timelines and shares these data in lessons learned sessions with the study teams.


    • The Data scientist acts as an expert for clinical and competitive databases being the contact for internal customers and external database providers including the response to database specific questions and the provision of feedback to available as well as evaluation of new databases. As such the Data scientist should coordinate database trainings in close cooperation with Feasibility Strategist and database provider(s).


    • Conducts scenario analysis using internal and external data with appropriate modelling tool to develop alternate scenarios with optimal site and country distribution based on robust data-driven rational. Identifies potential strategic (e.g. cost, timelines) operational (e.g. resource and start-up time) impact for each scenario and develop contingency plans.


    • Analyses survey responses and reviews recommendations received from external vendors and consolidate all data to formulate data driven and informed protocol and site feasibility recommendations.


    • Ensures that the information hub is fit-for purpose. Regularly monitors industry trends, regulatory requirements, technological advances, proactively scouts and evaluates new technologies and novel data from external and internal sources.


    • Participates in the development and augmentation of import filters, rules , methods and thesauri, manual correction of errors / problematic data, options for batch export & import to alternatively run data clean-up steps with external tools.


    • Works closely with internal functions to ensure that site performance, recruitment metrics and benchmark data are systematically collected, stored and utilized regularly.


Skill Set

  • Statistics background preferred with working knowledge of SPSS Modeler.
  • Candidates with experience and knowledge of Clinical Trial Process or Pharma background are preferred

You can mail your resume to
Job Role

Job Type

Interview Type

Face to Face Interview, Telephonic Interview

Company Description
    Focused on applying data mining techniques, performing statistical analysis, and building high quality prediction systems.
    Help solve manufacturing problems by conducting trend analysis, root cause investigations and process optimization. Bring innovative approach by developing sound hypotheses and proposing a sound design of experiments.
    Collaborate with the R&D and Clinical departments to optimize study designs and critical end points of clinical trials.
    Collaborate to develop an understanding and documentation of business problems, product requirements and success metrics.
    Work as a data strategist and predictive modeler, researching, identifying and integrating data sets and innovative Algorithms.
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