ARMMAN, Data Scientist
About the portfolio organization
ARMMAN is a non-profit organization that leverages technology to create scalable solutions empowering mothers and enabling healthy children. We are committed to improving the wellbeing of pregnant women, mothers and children in the first five years of their life. Our focus addressing systemic gaps to deliver better health outcomes for mothers and children through improved access to information and services along with capacity building of frontline healthcare workers.
About the Fellowship role
We are looking for a Data Scientist professional who can analyze ARMMAN Beneficiary Data, create Visual Model to show the effectiveness to all stake holders, produce various KPI reports, Develop AIU/ML Models for improving productivity.
Location: Delhi, India
Employment: Full-time, one-year Fellowship
Starting Date: 1 July 2023
Location: Delhi, India
Employment: Full-time, one-year Fellowship
Starting Date: 1 July 2023
Key responsibilities
- Assess the effectiveness and accuracy of data sources and data gathering techniques.
- Undertake pre-processing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms to increase and optimize beneficiary experiences
- Present information using data visualization techniques
- Develop custom data models and algorithms to apply to data sets
- Develop processes and tools to monitor and analyze model performance and data accuracy
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
- Lead other junior level Data Analysts and guide them on day to day activities
Requirements
We’re looking for someone with 5-7 years of experience data analytics and building AI/ML models, has a degree in Statistics, Mathematics, Computer Science or another quantitative field with following skills
Must Haves
- Proven experience as a Data Scientist or Data Analyst
- Experience in data mining
- Experience working with and creating data architectures
- Understanding of machine-learning and operations research
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Knowledge of SQL and Python to manipulate data and draw insights from large data sets
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
- Experience using web services: Redshift, S3, Spark, etc.
- Excellent written and verbal communication skills for coordinating across teams
- Analytical mind and business acumen
- Problem-solving aptitude
Must Haves
- Analyzed Large Database
- Developed Visual Representation using Tools
- Created AI/ML Models
- Should have very good written & oral communication skills
About the LGT Impact Fellowship
As part of LGT Venture Philanthropy's and Lightrock's strategic efforts to scale positive impact, the LGT Impact Fellowship was established to provide additional know-how and capacity to portfolio organizations and companies. Each year a limited number of professionals are nominated to work full-time for one year with the organizations and companies supported by LGT Venture Philanthropy and Lightrock in Latin America, Africa and India as per the above job description.
How to apply
Submit your application via the "Apply" button. Please note that we only accept online applications and that multiple applications are not allowed. However, you are invited to mention additional preferences in your application.
Moreover, please make sure to read all information in the application form carefully and answer the questions accordingly (additional information about the questions are marked with "i").
Moreover, please make sure to read all information in the application form carefully and answer the questions accordingly (additional information about the questions are marked with "i").
