Data Analyst

Full-time | Mission-driven | High-impact – 2 Positions

Do you believe that numbers can save lives, and want to turn data into real-world impact? About CEL

Community Empowerment Lab (CEL) is a globally recognised institution working to transform maternal and newborn health by uniting science with compassion. Our research-to scale pipeline powers India’s efforts toward single-digit neonatal mortality by 2030.

The Data Analytics & Decision Science Unit serves as the central nervous system of this pipeline, transforming raw, real-world field data into clarity, foresight, and lifesaving action.

Your Role

As a Data Analyst, you will help analyse complex datasets from research studies and programs, derive insights and communicate findings with compelling visualisations. You will work closely with the Team Lead of the unit, research and program teams.

You will:

• Identify available datasets to answer relevant research and programmatic questions
  

• Clean, manage, and analyse research datasets, as well as large, messy programmatic datasets
  

• Conduct regression analyses, risk modelling, survival analysis, and other statistical methods
  

• Identify early warning signals and leading indicators of maternal and newborn risk
  

• Support rapid-cycle evaluations and real-time decision-making
  

• Generate simple, intuitive dashboards, visualisations and analytical summaries
  

• Synthesise findings for diverse audiences, including researchers, program teams, and policymakers
  

• Collaborate with qualitative, implementation, and research teams to contextualise results
  

• Contribute to building a culture of analytical rigour, truthfulness, and learning
  

Who You Are

You may come from statistics, public health with a Master's/Bachelor’s degree, data science, economics, epidemiology, or any field that has trained you to think analytically and use statistical and analytical tools to solve problems with clarity.

We expect that you:

• Are a self-starter, with a demonstrated ability to frame analytical questions independently and select appropriate statistical approaches to answer them from a given dataset
  

• Have strong grounding in statistics, including regression, GLMs, causal thinking, risks & probabilities, survival analysis, multilevel modelling, etc.
  

• Are fully comfortable working in R and/or Python, and able to write reproducible, well-documented code
  

• Have experience cleaning and analysing large, messy, real-world datasets
  

• Understand missing, bias, confounding, and limitations of observational data
  

• Can communicate complex analyses in simple, meaningful ways
  

• Familiar with Dashboard tools like Shiny, Dash, etc.
  

• Willing to learn emerging analytical approaches, including AI-assisted workflows
  

• Are curious, disciplined, meticulous, thoughtful, and willing to learn continuously
  

• Bring humility, empathy, and respect for lived experience
  

• Have a genuine desire to make a difference in maternal–newborn health
  

Experience with analysing data from RCTs, large national surveys, health systems data would be a bonus.

You enjoy this role if you:

• Like working in complex systems where patterns emerge through exploration
  

• Often ask yourself questions like: “What is the story behind this data?”
  

• Feel comfortable with ambiguity and imperfect data
  

• Thrive in collaborative, cross-disciplinary teams
  

• Are you energised by the idea that your analysis might save a baby’s life next week?
  

• Believe that science becomes powerful when joined with compassion
  

Why join CEL?

• Contribute directly to a mission of national importance
  

• Influence maternal and newborn health outcomes at scale
  

• Work alongside visionary and compassionate leaders
  

• Grow within a living, learning, evolving system
  

• Experience an environment that values integrity, humility, curiosity, and deep purpose
  

Location

Varanasi/ Lucknow, Uttar Pradesh (India)

To Apply

Please share your CV with your email indicating the job title in the subject line. Only short-listed candidates will be invited to appear for interviews/s (virtual/telephonic/in-person).