Project Research Scientist I Non Medical (Senior Data Analyst)

As a Senior Data Analyst at CEL, you will be an integral part of the analyst team dedicated to gathering deep, high-quality insights on maternal child indicators influencing adverse health outcomes from implementation research and randomised controls trials. Your role will involve generating large amounts of primary quantitative data, organizing and analyzing it for decision-making and solutions. Key Responsibilities: - Analysis Plan and Dashboard Preparation: - Prepare the analysis plan document adhering to the study protocol and proposed analysis plan. - Identify the requirements for dashboards 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 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 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 and stakeholders. - Actively contribute to paper writing and dissemination efforts, ensuring the effective communication of appropriate insights. Qualification and Experience: - First Class Post Graduate Degree 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. - Applicants must be age 35 years or below as per ICMR age norms. - Proven experience in handling large datasets 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) for creating compelling visualizations and dashboards. - Proficiency in statistical analysis techniques, machine learning algorithms, and predictive modeling. - Knowledge of database management systems and proficiency in querying and extracting data from databases. - Strong analytical and problem-solving skills, excellent written and verbal communication skills, and attention to detail. - Understanding of research methodologies, industry trends, and capacity building of data team. - Experience in the ethical use of AI tools in research (chatGPT, etc.). **Additional De