Lead Data Analyst

WHAT WE OFFER

• Competitive Salary Packages
• Professional Development Opportunities
• Hybrid Work Setup
• Equipment Provided
• Day 1 HMO
• Life Insurance

POSITION OVERVIEW

The Lead Data Analyst is responsible for guiding a team of data analysts in delivering high-quality data analysis and insights that drive business decisions. This role involves a mix of technical expertise, leadership, and collaboration with stakeholders - internal (across the organization) and external (Payreto clients). The Lead Data Analyst plays a pivotal role in ensuring data quality, creating data visualizations and reports, and automating data processes. This role aims to spearhead Payreto's journey into adopting machine learning, computer vision, and advanced data analytics technologies as a part of our future growth strategy.

WHAT WILL YOU DO?

Leadership and People Management

• Lead a team of data analysts, ensuring the team's success and growth.
• Regularly conducts performance reviews and employee 1:1 to ensure alignment with standard of performance.
• Empowers team members to present quality work, facilitate harmonious working environment, and hone their skills
• Listens to team member's feedback and resolves any issues or conflicts;
• Embodies and Promotes the Team's 10 Commandments of Success (Team's work culture).
• Monitors employee concerns and disciplinary adherence;
• Leads the team members to attain established targets within the expected timeline.
• Hire and recruit team members inline with the expected team culture and competencies.
• Oversees the process of onboarding, developing, and leading of the employees from the department.

Operations and Account Management

• Serves as the primary point of contact for data analysis and interpretation for assigned projects.
• Coordinates with employees and clients regarding the details of the assigned projects for proper documentation of data findings
• Establishes processes, team targets, and project timelines.
• Ensures the team's performance adheres to the established processes and procedures.
• Ensures that the team reaches the Client's targets and no escalations have been set-up.
• Assist the team in any data related questions.
• Maintains and initiates strong, long-lasting client relationships by establishing rapport and building trust.
• Prepares and designs reports for clients and management regarding project status, data trends, and data findings
• Develops new projects with existing clients and/or new working relationships with new clients
• Addresses client concerns, requests or issues as needed, especially escalations

Strategy and Product Vision

• Helps shape the organization's data-driven strategies through data insights and analysis.
• Helps, proposes, and builds necessary data infrastructure to help generate a more organized data infrastructure or client strategy.
• Writes memos / documentations on proposed data set-up for the whole organization.
• Identifies product and service related opportunities for the data analysis tasks.

Technical Expertise (Full Life Cycle of Data Analysis)

• Understands different data and provides guidance in working on them.
• Designs and creates interactive dashboards using tools like PowerBI or Google Looker Studio.
• Provides practical expertise in automating tasks with Python scripts and shows a solid understanding of fundamentals.
• Shows hands-on experience in different stages of the data lifecycle. Including data collection, data cleaning, management, manipulation and data visualization.
• Understands Familiarity with different Python libraries such as pandas, NumPy, and Maplotlib.
• Uses advanced use of Excel, including pivot tables, complex formulas, VBA macros, and data analysis functions.
• Develops, documents and implements data control necessary for the installation and administration of the departments on-line data processing systems
• Conducts data mining activities, such as collecting and organizing data from multiple sources in order to identify patterns or other useful information.
• Analyzes data to identify patterns, trends, or other meaningful insights in order to make
  recommendations for improvement.
• Oversees the creation of dashboards that are needed by the business stakeholders.
• Supervises the design and preparation of various statistical reports.

Communication and Reportings

• Stakeholder Collaboration. Work with cross-functional teams, including business stakeholders, business development team, and other departments, to align on goals and objectives.
• Communicates findings to clients, including presenting reports in written or verbal format.

Other Tasks

• Assist in other ad hoc topics and projects as assigned by the immediate supervisor.
• Recommend and proactively implement opportunities for increased departmental efficiency.
• Extend work hours when needed.

WHAT SHOULD YOU HAVE?

• A bachelor's degree preferably in a relevant field such as Data Science, Statistics, Computer Science, Mathematics or Information Technology, Economics.
• 3-5 years of experience in data analysis, ideally with a progression into leadership roles.
• Experience in managing data projects from start to finish, including planning, execution, and delivery.
• Experience leading a team of data analysts or similar roles.
• Hands-on experience in data analysis tools from Excel to using programming languages like Python. Involvement in Data Manipulation, Cleaning, Collection, Data Visualization.
• Ability to create a clear and insightful visualization using tools like Tableau, PowerBI, or Python libraries such as Matplotlib and Seaborn.
• Ability to analyze complex datasets, identify trends and derive actionable insights.
• Strong problem-solving to tackle data-related challenges.
• Ability to align data analysis with business goals and objectives.
• Agile: Able to adjust in a fast-paced environment and show flexibility.
• Forward-thinking mindset: Encourages the growth of the company and its people.
• Fosters analytical and critical thinking.
• Possesses leadership skills and managing people toward the success of projects.

NICE TO HAVE:

• Relevant certifications such as Certified Analytics Professional (CAP), Microsoft Certified: Data Analyst Associate, or Google Data Analytics Professional Certificate.
• Proof of work from previous employment like projects and tasks or education.
• Portfolio showcasing projects displaying usage of different tools and skills.
• Has worked with Clients from Western Countries such as (UK, US, EUROPE, Australia).

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