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Job Description

Data Modelling Specialist

Foundation for Innovative New Diagnostics

New Delhi

1. POSITIONS VACANT: Data Modelling Specialist, Foundation for Innovative New Diagnostics (FIND) India, New Delhi




The Foundation for Innovative New Diagnostics (FIND), is established in India as an independent, non-profit, created under Section 8 (Indian) Companies Act, 2013, with its office in New Delhi. FIND India is the key implementing partner of Central TB Division, Ministry of Health & Family Welfare, Government of India, for strengthening and expanding TB laboratory diagnostic capacity under the National Tuberculosis Elimination Program (NTEP) with the support of the Global Fund.


FIND India, the global alliance for diagnostics, seeks to ensure equitable access to reliable diagnosis around the world. FIND connects countries and communities, funders, decisionmakers, healthcare providers and developers to spur diagnostic innovation and make testing an integral part of sustainable, resilient health systems. FIND is working to save One million lives through accessible, quality diagnosis, and save US$1 billion in healthcare costs to patients and health systems. FIND is a co-convener of the Access to COVID-19 Tools (ACT) Accelerator diagnostics pillar, and a World Health Organization (WHO) Collaborating Centre for Laboratory Strengthening and Diagnostic Technology Evaluation.


For more information about the organization, please visit http://www.finddx.org/




The SARS-CoV-2 pandemic continues to ravage the World and India in 2021 and is a great threat to global public health.  As of 16 August 2021, 205 million cases and >4.3 million deaths have been confirmed globally. In India, ~32 million confirmed cases have been reported so far  with a rapid increase in the number of new cases during the “second wave”  in the last few months. Daily cases touched highs of >300K, the highest in the World, during the last wave with delays noticed in every part of the care continuum including massive delays in testing. The SARS-CoV-2 pandemic highlights huge gaps in the testing capacity - a key element for timely isolation of infected persons and prevention of infection propagation in the community. Current testing challenges include sub-optimal capacity and utilization of COVID-19 testing network, scarcity of efficient models for enhancing lab capacity, inefficiencies within laboratories to facilitate rapid turnaround of quality tests, lack of coordination between public and private sectors to amplify and optimize India’s laboratory capacity and shortage of trained manpower at the COVID-19 labs. This makes delays in diagnosis of SARS-CoV-2 infections a critical point of failure in the COVID-19 strategic preparedness and response plan.




FIND proposes to provide a comprehensive package of activities as part of the USAID supported Project Reaching Impact, Saturation, and Epidemic Control (RISE) project to systematically address gaps in diagnostic capacity, availability, access and quality of testing as well as implementation of current genome sequencing guidance as issued by the INSACOG.


Project approaches include:


(1) Conducting of a situational analysis to identify key diagnostic needs and conduct a capacity assessment of the states identified under the project;

(2) Technical assistance for effective implementation of ICMR testing guidance around operationalization of ICMR laboratory guidance, including development of documentation and reporting tools, capacity building, implementation of testing & quality assurance (QA) strategies:


(a) Estimation of future demand for COVID-19 testing and visualization of existing labs and capacity.

(b) Predictive modelling of testing demand – multiple scenario generation;

(c) Models of optimized Sample referral system.

(d) Recommendations on rationalisation of equipment – placing high throughput/additional equipment, re-purposing equipment under other disease programs to leverage unutilized capacity etc.

(e) Supplementing RT-PCR testing with Rapid antigen testing strategies;


(3) Capacity building via a mix of on-site/assisted and online methods for trainings:

(a) Online Learning: training site staff via online courses allowing the project to circumvent effects of COVID-19 pandemic and related travel restrictions. Approaches include assisted e-trainings, webinars and panel discussions;

(b) Onsite/assisted trainings to supplement the online content with a focus around specific aspects of testing, reporting, troubleshooting, preventive maintenance, biosafety, sequencing guidelines/implementation etc as identified as during situational analysis;

(4) Digital Solutions to support automation of testing processes and data management for rapid antigen tests (RAT) testing, the project will deploy open-source digital applications that can be easily transitioned to states;

(5) Advocacy activities for continued testing, private sector engagement approaches and cross-sharing of learning.


Objective and Primary Outcome:

Against the background and rationale stated above, FIND as Sub Recipient to JHPIEGO, will use various technical assistance approaches to implement activities identified under the project. The project will deploy a learning laboratory approach in the 3 intervention states and further propagate learnings and best practices to remaining states as covered by USAID’s RISE project.




The Data Modelling Specialist will lead implementation of the diagnostics network optimization exercise under the RISE project aimed at increasing access to diagnostic services in select states, and to inform new diagnostics development and roll-out strategies. The incumbent will be expected to use analytical and quantitative methods to understand, predict and enhance processes to optimize access to health diagnostic services and communicate their outputs using data visualization and detailed reports.


Key Job Responsibilities:

(1) Independently working on one or more analytical tools like Excel, R, Python, SQL, Tableau for analysing data sets and presenting findings related to national health programmes and diagnostic networks. S/He will be expected to understand, test and troubleshoot SAAS tools being developed for optimizing diagnostics networks;

(2) Become proficient in and independently utilize the open access OptiDx tool developed by FIND and partners, for building and analysing State-level models for diagnostic network strengthening around forecasting demands, rationalising existing resources and current and future extra resources required. This would include modelling for number and type of testing sites, equipment;

(3) Support use of the OptiDx tool (and contribute to enhancement of its parameters, to help optimize diagnostic networks for COVID-19  diagnostic program and implementing partners;

(4) Work with partners at JHPIEGO/ state level partners to support collection of relevant data to support the objectives of diagnostic network optimization projects;

(5) Work with relevant government stakeholders in the project districts to define specific state level objectives and optimization parameters, boundary conditions etc.;

(6) Provide training and coaching support to selected personnel at the RISE hubs around data collection, modelling;

(7) Compile and interpret data relevant to the diagnostic network optimization project objectives (demand patterns, costs, productivity, etc.);

(8) Assess available data, identify data gaps and limitations, and proactively suggest and implement approaches to clean and integrate data. Suggest assumptions to fill identified data gaps along with justification for them;

(9) Identify, analyse, and interpret trends or patterns from the national data and share reports with relevant project stakeholders.

(10) Provide data analysis support for the writing of publications and scientific presentations;

(11) Regularly update the Project manager and other team members on the progress and difficulties experienced.





Applicant must have Bachelor’s degree (Masters preferred) in biostatistics with a strong data element, computer science, information management, data science and analytics, or related data-intensive field.



(1) Atleast five years relevant experience of working with large data sets in data management and/or data analytics roles including independently handling data collation, cleaning, validation and analysis, including one year in data modelling.


Skills and Competencies

(1) Ability to develop and institutionalize operational processes and controls;

(2) Ability to understand and define processes;

(3) People/Team Management skills;

(4) Proven management skills with the ability to optimise team performance
and development;

(5) Advanced problem solving, analytical, and quantitative skills, including significant experience working with Excel;

(6) Ability to select the right tool for analyses e.g. quick analyses using MS Excel, or more detailed analyses using statistical software such as R or Python. Ability to present insights in easily understood data visualizations using software such as Tableau;

(7) Willingness to expand knowledge base and take on new topics;

(8) Work well in teams of multi-cultural backgrounds; effective communication;

(9) Superior problem-solving skills and detail oriented;

(10) Represent the FIND strategy and goal of being an honest, transparent broker in the global health field.

(11) Willingness to travel if required and at short notice.




The gross remuneration budgeted for the position is attractive and shall be commensurate with the qualifications, experience, and salary history, of the selected candidate.






The successful candidate shall be issued an employment contract for the duration of 13 months from the date of joining and shall be renewable subject to satisfactory performance, project extension and fund availability.







Strategic Alliance Management Services P Ltd.

1/1B, Choudhary Hetram House, Bharat Nagar

New Friends Colony, New Delhi 110 025

Phone Nos.: 2684 2162; 4165 3612




Eligible candidates interested in this position are requested to apply online to https://recruitment.samshrm.com/JOBS/FIND at the earliest.