Senior Data Analyst

CEL is now looking for Senior Data Analysts. We are building a dedicated analyst team to gather deep, high-quality insights on maternal and child indicators influencing adverse health outcomes from implementation research and randomized control trials. This will entail the generation of large amounts of primary quantitative data that will need to be organized and analyzed for decision-making and solutions. This is where our Data Analysts step in. You will be at the heart of our data center, watching the flow of data and helping to channel it for decision-making.

Since our study area consists of families that have Hindi as their native language, communication in Hindi and local dialect would be desirable. Proficient communication in English would be appreciated for engaging in formal communication, especially with foreign partners and stakeholders.

Scope of Work:

• Analysis plan and dashboard preparation: Prepare the analysis plan document adhering to the study protocol and analysis plan proposed. Identify the dashboard requirements and develop them.
• Data collection planning: Collaborate with the research team to define data requirements, sources, and collection methods. Participate in data collection protocols and tools to ensure accurate and reliable data acquisition.
• Data cleaning and preprocessing: Conduct data cleaning and preprocessing activities to identify and address errors, outliers, and missing values in the dataset.
• Data analysis and interpretation: Conduct advanced statistical analysis and data mining techniques (regression, multivariate, time series, survival, inferential, cluster, classification, etc.) to analyze research data. Interpret findings, identify trends, and derive actionable insights to support research objectives and hypotheses.
• Model development and validation: Develop predictive models, algorithms, and statistical models to analyze complex datasets and forecast future outcomes. Validate model performance and accuracy using appropriate validation techniques.
• Data visualization and reporting: Create clear and insightful data visualizations, dashboards, and reports to communicate research findings to stakeholders. Present findings in a compelling and understandable manner to facilitate decision-making.
• Quality improvement of team: Prepare and share regular data findings reports with the project team for continuous improvement of data quality.
• Collaboration and communication: Collaborate with interdisciplinary project teams, including PI, Co-PIs, researchers, project management team, and domain experts, to align data analysis activities with research goals. Communicate technical concepts and findings effectively to non-technical stakeholders.
• Project management support: Provide support to project managers in planning and executing data analysis activities. Track project timelines, milestones, and deliverables to ensure timely completion of analysis tasks.
• Continuous learning and skill development: Stay updated with the latest advancements in data analysis methodologies, tools, and technologies. Continuously enhance technical skills and domain knowledge to improve data analysis capabilities.
• Quality assurance and documentation: Ensure adherence to data quality standards, best practices, and regulatory requirements throughout the data analysis process. Document analysis methodologies, assumptions, and limitations for reproducibility and transparency.
• Mentorship and training: Provide guidance and mentorship to junior data analysts and research team members. Conduct training sessions and workshops to share best practices, tools, and techniques in data analysis.
• Consolidate findings, dissemination of results, and manuscript writing: Synthesize research findings into actionable insights, compelling narratives, and data-driven recommendations for the internal team as well as stakeholders. Actively contribute to paper writing and dissemination efforts, ensuring the effective communication of appropriate insights. Support researchers in manuscript writing.

The Senior Data Analyst leads the analysis and will have significant coaching and mentoring responsibilities for the team.

Travel: Willingness for travel, both locally and out of the city as required.

Qualification and Experience:

• First Class Post Graduate Degree, including integrated PG degrees, in B.Tech/MCA/M.Sc (Maths/Stats)/Master in Population Science/Master in Public Health/Master in Business Administration with three years of experience OR PhD.
• Diploma in Analytical Sciences will be an advantage.
• ICMR age norms will apply; applicants must be age 35 years or below.
• Proven experience in large dataset handling and advanced analysis.
• Experience in manuscript writing, publication, and dissemination of research findings in peer-reviewed journals and conferences.

Necessary knowledge and skills:

• Good working knowledge and hands-on experience in advanced data analysis using STATA/SPSS.
• Advanced skills in data manipulation and programming languages such as Python/R, SQL.
• Proficiency in data visualization tools and libraries (e.g., Tableau, matplotlib, ggplot2) to create compelling visualizations and dashboards.
• Proficiency in statistical analysis techniques, including hypothesis testing, regression analysis, clustering, and classification.
• Experience with machine learning algorithms, data mining techniques, and predictive modeling.
• Knowledge of database management systems (e.g., SQL Server, MySQL) and proficiency in querying and extracting data from databases.
• Strong analytical and problem-solving skills to tackle complex research questions and data challenges.
• Excellent written and verbal communication skills to convey technical concepts and research findings to diverse audiences.
• Ability to manage multiple projects simultaneously, prioritize tasks, and meet deadlines in a fast-paced research environment.
• Keen attention to detail and commitment to data accuracy and quality assurance.
• Understanding of research methodologies, domain-specific concepts, and industry trends relevant to the research project.
• Ability to architect strategy along with leadership skills and capacity building of the data team.
• Competence to build and effectively manage interpersonal relationships at all levels of the organization.
• Experience working in a research organization is an added advantage.
• Experience in the ethical use of AI tools in research (ChatGPT, etc.).

Skills

Analysis, Data