Senior Data Analyst

ABOUT YOU

We expect you to be a high-level technical lead tasked with managing projects within the analytics team. The successful candidate will efficiently and effectively organize projects, coordinate and assign resources, track the logistics of projects, and deliver high-quality results for our clients.

Minimum Qualifications and Experience Requirments:

• Bachelor’s degree in Statistics, Mathematics, Actuarial Science, Computer Science or related field. Master’s degree in related field is desired.
• Minimum 6 years of relevant experience with at least 2 years in a supervisory role.
• Advanced knowledge of Microsoft Office Suite – advanced Excel, Word and PowerPoint skills.
• Expertise with at least one data analysis software such as IBM SPSS Statistics, R, Stata or SAS.
• Expertise with statistical methods that includes descriptive and inferential statistics.
• Advanced knowledge of data visualization tools such as Power BI, R Shiny Dashboard or Tableau.
• Communicating clearly via written and spoken English.

Skills and Key Competencies:

• Practical knowledge of descriptive and inferential statistics.
• Excellent written and oral communication and presentation skills.
• High accuracy and attention to detail factoring every piece that might alter the validity of data.
• Ability to provide gainful insights and pragmatic solutions to Dalberg Research clients with a bias towards action and resolving issues quickly.
• Ability to handle multiple tasks and meet tight deadlines.
• Excellent creative and innovative problem-solving skills.
• Natural ability to get along with people and establish strong and meaningful relationships with others.
• Be self-motivated and proactive in executing the assigned roles.
• Unquestionable integrity, confidentiality and respect.

WHAT YOU WILL DO

The Senior Data Analyst will be reporting to the Data Processing Manager and will supervise a team of data processing executives and junior data processing executives who perform high-level data management and analytical work, and complete high-priority projects across an array of domains and subject matter.

In addition, you will be an active member of the internal team, contributing to internal knowledge sharing, best practice development and team engagement. This is a great opportunity to use your existing data analysis and team leadership skills, while growing your capabilities within a rapidly expanding company.

KEY RESPONSIBILITIES:

• Responsible for the delivery of projects within the analytics team in liaison with the Data Processing Manager (DPM).
• Provide innovative analytical insights to Dalberg Research clients.
• Work closely with the DPM in ensuring constant compliance with standards and to effect change where merited within the data processing department.
• Break down project problems in a clear and concise manner to the junior staff for execution.
• Oversee the activities of the junior staff within the analytics team and ensures efficient execution of their duties.
• Identify, evaluate, and document potential data sources in support of project requirements.
• Advise clients and project teams on relevant statistical approaches such as descriptive statistics, hypothesis testing, diagnostic analysis as well as predictive modelling.
• Use statistical tools to interpret data sets, paying attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.
• Ensure that data analysis processes are properly documented to improve transparency and for future references.
• Create data visualizations to effectively convey findings using Power BI, R Shiny Dashboard or Tableau.
• Document data analysis results in a clear and concise manner.
• Present data analysis findings to project teams or clients whenever requested.
• Develop and implement data processing quality control procedures that optimize efficiency and quality.
• Liaise with client service team during proposal writing to inform on data quality control procedures, data cleaning processes and data analysis.
• Work closely with the data processing manager to train junior data processing staff on statistical methods and generation of insights from data.
• Improve existing SOPs and standardize Data Processing operations that are not yet standardized.