• Designing and implementing Data Engineering solutions for clients both on-premises and on the cloud for clients using platforms like Databricks, Azure and AWS. This involves making effective use of tools like Data Factory, Spark on Databricks, AWS EMR
• Designing and implementing Data Science & AI solutions for clients both on-premises and on the cloud using tools like Azure Synapse, Azure Machine Learning Studio, Amazon Sagemaker, etc.
• Implementing Data Engineering Solutions using Apache Spark (PySpark) and orchestrating the data pipelines using Apache Airflow or Dagster.

• Product Analytics:
-Building business metric tracking systems to track performance of various productsand key drivers of performance.,
- Creating and working on descriptive, predictive, and optimization models to enhancerevenue generation, customer retention and churn reduction.
• Building Data Analytics and Business Intelligence System for Equals. Microsoft Power BI.
• Building and supporting corporate Data Warehouse.
• Building and implementing Machine Learning algorithms for credit scoring in production.
• Building Data Pipelines to support organizational data analytics use cases. Data pipelines weredeveloped using Apache Spark (PySpark) and Apache Airflow.
• Building and supporting real time data processing pipelines using Apache Kafka and ApacheSpark. The pipeline is used for tracking liquidity and limit utilization for all the creditproducts for Equals.
• Demand forecasting: This involves forecasting liquidity and revenue for various producttypes.
• Writing various automation scripts for data processing in Python and orchestrating them usingApache Airflow.

• Leading Junior Data scientists and analysts and mentoring them in the field of Data Science. This involved creating various training programs aimed at equipping them with skills to do advanced analytics.
• Building Machine learning models for subscriber segmentation and credit scoring. This involved deploying the models into production. This involved deploying the models and implementing the data processing pipelines on Azure.
• Identifies and executes appropriate analytical techniques and data science methodologies and algorithms to provide in-depth analysis of transactional, subscriber and aggregated data including prescriptive and predictive models.
• Identifies and prepares structured and unstructured data from various internal and external sources to determine/test its value when applied in algorithms.
• Collaborates with the data engineering department to identify data scrubbing and enrichment projects, determine the requirements for these projects, agree solutions and test outcomes
• Report on and present findings on algorithm development including the quantification of its business impact
• Perform in-depth analysis to identify leading indicators of subscriber behaviour (e.g. churn, credit risk, purchases) and develop propensity models to pre-emptively target subscribers
• Prepare and build scenario-based business models to evaluate the financial feasibility of campaigns
• Present findings of campaign recommendations, and costs to test recommendations to business
• Monitor and report on impact of campaigns post launch
• Scope and provide the data science requirements for the operationalization of thealgorithms/data science/analytical projects, including the provision of metrics, attributes,logical rules and algorithms
• Conduct thorough user acceptance testing on automated solutions including reviewing thealgorithms, recommendations made and financial feasibility of the latter.
• Developed and automated various Robotic Process Automation tasks using UI Path andPython related OCR tools.

a. Product Pricing, Valuations and Financial Modelling
i. Providing business assumptions for financial planning purposes and financial modelling.
ii. Pricing and valuations of new products, projects and Cumii Business.
iii. Building financial models and projections for valuations and Cumii Group Budgets.
iv. Preparing Cumii Group Budgets and Forecasts for all business verticals and markets
v. Assessing funding requirements and producing funding requests applications to Banks and Financial Institutions.
b. Business Analysis & Reporting:
i. Develops performance metrics to evaluate progress toward achieving Cumii strategic goals.
ii. Develops financial and statistical-based models to analyse business performance trends and insight into operational effectiveness and efficiency.
iii. Prepares formal quantitative and qualitative analyses for decision support on high-priority strategic issues.
iv. Coordination of relevant stakeholders in defining scope of business requirements
v. Prepares monthly executive management operations review presentation
vi. Develops Executive reporting dashboards to track the performance of key performance indicators
vii. Weekly, monthly, and annual operational performance review reporting
c. Risk assessments, analysis, and reporting for the organization
d. New product development and enhancement through data driven insights including addition of value-added services to main product

a. Developing and implementing databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
b. Interpreting data, analysing results using statistical techniques and providing ongoing& ad-hoc reports & ad-hoc. This involved data cleaning, analysis, reporting and producing ad-hoc reports.
c. Producing daily, weekly and monthly reports for management regarding various aspects of connected lifestyle products
d. Work with management to prioritize business and information needs and ensuring proper internal controls are in place that minimize operational risks.
e. Analysing customer queries and complaints on an ongoing basis and making recommendations to the management.
f. Competitor, market analysis and risk assessments for the products.

a. Designing Modules for Personal Financial Management to be used in Personal Financial Management Workshops by the Organization.
b. Facilitating Business Strategic Planning Sessions with Clients.
c. Helping clients understand the internal risks and external risks they are exposed to and makingrecommendations on how to best manage them.
d. Presenting in Leadership workshops on various topics related to risk management and internal controls

a. Risk Analysis & Assessments:
i. Carrying out risk assessments and analysis for clients’ existing and new products and givingrecommendation for mitigation measures.
ii. Risk analysis after carrying financial reviews of Insurance products and Pension Funds.
iii. Carrying out compliance assessments of Pension Funds and Life Insurance Companies and making comparisons with the standards regarding Reserves set by IPEC.
iv. Liaising with Compliance Bodies like IPEC on Minimum Reserve Requirements for insurance products and all regulatory issues.
b. Life Insurance Products:
i. Pricing, valuation and profitability analysis of life insurance products
ii. Participate in product development for new life insurance products for clients.
iii. Developing pricing and valuation models for use in all actuarial valuations and producing reports
iv. Liaising with clients and address all issues that would have emerged in the process of data checksand valuations.
v. Attending to queries from clients regarding things like surrender value calculations and ongoingqueries.
c. Pension Funds:
i. Developing models for carrying out financial reviews for pension funds and producing reports for clients summarising the financial review exercise.
ii. Carrying out audits of the benefits and payments made by Pension Funds and clients during accounting period to see whether they are in line with standards set by regulatory bodies like IPEC.
iii. Data reconciliations, analysis of emerging surplus and reviewing work done by fellows.
iv. Liaising with clients continuously and resolve emerging queries and attending to queries on anongoing basis
d. Data Management & Analysis:
i. Data collection and capturing from various sources for use various actuarial work, e.g., in assessing the performance of Pension Funds’ assets.
ii. Acquiring data from primary or secondary data sources and maintaining databases systems.
iii. Identifying, analysing, and interpreting trends or patterns.