Data Consultant at Dentsu

Key responsibilities:

Audience Creation & Segmentation:

• Collaborate with stakeholders to define target audiences based on business objectives.
• Use analytics tools to design, build, and segment customer audiences that support marketing and business strategies.
• Regularly refine and optimize audience segments to enhance campaign effectiveness.

Business & Data Translation:

• Act as a bridge between business teams and data specialists, translating business needs into technical requirements and data insights.
• Work closely with marketing, product, and other departments to ensure data solutions are aligned with business goals.
• Conduct workshops and brainstorming sessions to identify data opportunities and communicate findings to non-technical stakeholders.

Technical Coding & Data Manipulation:

• Write, maintain, and troubleshoot code (Python, SQL, R, or similar) for audience segmentation, data extraction, and transformation tasks.
• Develop and manage custom data solutions to support advanced segmentation, predictive modeling, and campaign performance analysis.
• Ensure data integrity and accuracy by implementing data quality checks and validation procedures.

Insights Generation:

• Leverage data analytics to produce actionable insights, such as customer behavior patterns, trends, and campaign performance analysis.
• Present insights to business leaders in an easily understandable manner, offering strategic recommendations for improvement.
• Track and report on key metrics, providing timely and accurate insights that support data-driven decision-making.

Collaboration & Communication:

• Collaborate with data engineers, data scientists, and IT teams to ensure smooth data pipeline operations and data availability.
• Partner with business stakeholders to understand and prioritize their data needs and maintain a continuous feedback loop for improvement.
• Advocate for data-driven solutions within the business, promoting the value of data analytics in achieving business objectives.

Key Skills & Qualifications

• Educational Background: Bachelor’s degree in Data Science, Computer Science, Business Analytics, or a related field.
• Experience: Minimum 3 years in a data-focused role within a financial institution, consulting firm, or tech environment.
• Technical Skills: Proficiency in SQL and Python (or similar scripting languages); experience with data visualization tools like Tableau or Power BI is a plus.
• Audience Segmentation: Hands-on experience in creating and managing audience segments, ideally within a banking or financial services context.
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret complex data sets and translate them into actionable insights.
• Communication: Excellent verbal and written communication skills, with the ability to effectively engage both technical and non-technical audiences.
• Team Collaboration: Demonstrated experience working in cross-functional teams, with the ability to lead data projects from concept to completion.

Preferred Qualifications

• Experience in banking or financial services, with familiarity with customer segmentation and campaign analytics.
• Knowledge of data governance, data privacy regulations, and compliance in a financial institution.
• Advanced experience with audience creation, predictive analytics, and data-driven marketing strategies.