Adel Megdyatova

Data Strategy Development: Spearheaded the formulation and execution of a robust data strategy that seamlessly aligned with the overarching business objectives across 5 subsidiaries

Data Governance Management: Oversaw and ensured the precision, uniformity, and security of organisational data through the enforcement of global policies and standardized data management procedures.

Data Regulation Compliance: Ensured full compliance with the data regulations for Australia and NZ Privacy Act, PCI DSS, CCCFA, ASIC

Leadership in Data Initiatives: Collaborated closely with key stakeholders to drive and implement impactful data-driven initiatives, encompassing areas such as data analytics, governance, security, and the promotion of a data-centric culture.

Effective Team Management: Proficiently managed data-focused teams across 4 locations

• Designing the data infrastructure, system requirements and data warehousing for a major NZ roading project that included IoT sensors, video and picture data streams, multiple system integration

Global Team Leadership: Successfully managed a diverse, cross-geography team spanning Australia, New Zealand, and the Philippines, fostering collaboration and achieving project excellence.

Predictive Modeling and Machine Learning Expertise: Developed and deployed 30 predictive models and machine learning algorithms, maintaining their performance through continuous monitoring and recalibration.

Advanced Data Solutions for Business Growth: Innovatively created advanced data solutions that enhanced revenue, reduced operational costs, and optimized overall business profitability.

Business Stakeholder Engagement: Demonstrated the value of data science to business stakeholders by automating processes, generating insightful reports, constructing predictive models, and delivering actionable insights.

Multi-Source Data Integration: Effectively integrated data streams from diverse sources, including telephony, text, web click data, and disparate systems, ensuring data consistency and reliability.

Scalable Data Structures and Machine Learning: Delivered high-scale, reusable data structures and concepts while also building and deploying machine learning algorithms, including decision trees and random forests.

Infrastructure Enhancement Leadership: Identified, scoped, and spearheaded infrastructure improvement initiatives, enabling the implementation of advanced analytical solutions.

Global Collaboration and Peer Reviews: Collaborated with the Decision Science team in the US, conducting peer reviews and ensuring alignment with global analytics strategies.

Comprehensive Team Management: Led and supervised a geographically dispersed team of Data Scientists, Data Engineers, Reporting and Data Analysts across Sydney (Australia), Auckland (NZ), and Manila (Philippines).

Data-Driven Stakeholder Collaboration: Established data-driven collaborations among internal and external stakeholders, fostering information sharing and synergies.

Team Building and Leadership: Built and nurtured high-performing teams, empowering team members to excel in their roles.

Data-Driven Insights and KPI Tracking: Identified and presented trends, leading indicators, KPI trends, and patterns, driving data-informed business improvements.

Data Infrastructure Projects: Successfully delivered data warehousing and data infrastructure improvement projects, including server installations, SAS infrastructure, PII data handling, security implementations, data governance, and reporting and dashboarding.

Tool Implementation and Vendor Management: Led the implementation of key tools such as Salesforce, Tableau, R Studio, KNIME, and SAS, while efficiently managing vendor relationships.

Tender Writing and Client Presentations: Spearheaded tender writing efforts and delivered compelling client presentations, showcasing technical expertise and value propositions.

Effective Project Delivery: Demonstrated consistent success in project delivery, ensuring projects were completed on time and within scope.

• Assisting an organisation very early in their data journey to start creating data, formulating KPI and metrics to track
• Designing data flow and reporting
• Uncovering and presenting insights/recommendations

• Working with a premium NZ natural skincare company to develop their export strategy.

• Working with a NZ meal kit company to identify future growth opportunities including overseas expansion

• Calibrating strategies
• Managing client relationships
• Workshop facilitation and change management
• Provided analytically driven solutions to improve financial outcomes
• Provided portfolio segmentation and insights to drive client process improvements
• Responsible for achieving revenue and costs targets, forecasting
• Developing strategies in line with performance requirements
• Tender writing & presentationsC to Country Manager
• Optimising performance and metrics
• Setting performance targets and KPIs
• Mentoring staff
• BAYCORP
• EMPLOYEE OF THE YEAR 2019

Data Collection:

Gather data from various sources, including databases, spreadsheets, and external datasets.

Develop and maintain data collection and data quality processes.

Data Cleaning and Preprocessing:

Clean, validate, and transform data to ensure its accuracy and reliability.

Handle missing data and outliers appropriately.

Data Analysis:

Conduct exploratory data analysis (EDA) to understand data patterns, trends, and anomalies.

Perform statistical analysis to identify correlations and insights.

Data Visualization:

Create visual representations of data, such as charts, graphs, and dashboards, to communicate findings effectively.

Data Interpretation:

Extract meaningful insights from data and translate them into actionable recommendations.

Collaborate with stakeholders to ensure data-driven decision-making.

Report Generation:

Generate reports and summaries of analysis findings.

Prepare and deliver presentations to convey results to non-technical audiences.

Data Modeling and Forecasting:

Forecast future trends and outcomes based on historical data.

Data Security and Compliance:

Ensure data privacy and compliance with relevant regulations

Implement data security measures to protect sensitive information.

Database Management:

Manage databases and data storage systems.

Optimize database queries for performance.

Data Governance:

Establish and enforce data governance policies and procedures.

Maintain data dictionaries and metadata.

Continuous Learning:

Stay updated on industry trends, data analysis techniques, and tools.

Collaboration:

Collaborate with cross-functional teams, including data engineers, data scientists, and business stakeholders.

Define data requirements for projects and provide support to team members.

Problem Solving:

Identify data-related challenges and propose solutions.

Troubleshoot data issues and anomalies.

Documentation:

Document data analysis processes, methodologies, and findings.

Maintain organized and accessible documentation.

Data Validation and Testing:

Validate data accuracy and reliability through testing and validation procedures.

Data Storytelling:

Craft compelling narratives around data insights to influence decision-makers.

A/B Testing and Experimentation:

Design and analyze A/B tests and experiments to evaluate the impact of changes or interventions.

Data Quality Assurance:

Monitor and ensure the quality of incoming data.

Develop and maintain data quality metrics.

Data-driven Recommendations:

Provide actionable recommendations based on data analysis to drive business improvements and strategies.

Project management (client take on, systems implementation, process improvement, legacy systems transition)

Gathering client requirements and creating analytically driven system and process solutions

Led projects that drove improvements and customisations for the main CRM system

Designing and building internal and external reports, dashboards, analytical presentations

• Legacy systems transitions, IT and process change management
• Developing and applying solutions for existing and potential client problems
• Identifying risks and implementing solutions
• Data extraction, cleansing, analysis and reporting
• Monthly client reports
• Impelementing improvements to the data availability
• Liaising with stakeholders at all levels
• Identifying and implementing operational solutions