Data and Business Insights Analyst

at  NTT Data

Req ID: 299539
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

JOB TITLE: DATA AND BUSINESS INSIGHTS ANALYST

Remote working, UK
About the Team: We are a dynamic, forward-thinking team dedicated to leveraging data to drive strategic business decisions, with a strong emphasis on empowering our clients. Our innovative approach to data analytics helps businesses unlock new opportunities, optimize operational efficiency, and make data-driven decisions. Collaboration, creativity, and a passion for excellence are at the heart of what we do, and we are constantly striving to push the boundaries of data consultancy.
Position Overview: We are seeking a Data Consultant with strong analytical and client-facing skills to join our expanding team. This is an exciting opportunity to work closely with senior consultants and clients, particularly in the banking and financial services industry, to provide insightful data-driven strategies that shape business outcomes. You will play a pivotal role in helping our clients navigate complex datasets, uncover critical insights, and apply tailored data solutions that drive real-world business results.
This position offers the perfect blend of technical data expertise and client-facing interaction, ideal for someone who thrives in a fast-paced, collaborative environment. As a Data Consultant, you will contribute to various stages of data consultancy, from data collection and cleaning to presenting actionable insights, all while ensuring alignment with client goals and industry best practices.

QUALIFICATIONS:

• Degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related field.
• Experience in data analysis, business intelligence, or a related role.
• Proficiency in SQL, Python, R, and/or Excel for data analysis.
• Experience with data visualization tools like Tableau, Power BI, or similar platforms.
• Strong analytical and problem-solving skills with the ability to interpret complex data and make recommendations.
• Proven ability to communicate data insights clearly and concisely to non-technical stakeholders.
• Experience with data warehousing and database management tools is advantageous.
• Familiarity with machine learning techniques and statistical analysis is a plus.
• Excellent attention to detail and ability to manage multiple tasks in a fast-paced environment.

PREFERRED SKILLS:

• Exposure to the banking industry or a solid understanding of financial data and metrics is beneficial.
• Experience with big data technologies and Knowledge of cloud computing platforms like AWS, Azure, or Google Cloud is a plus.

• Collaborate with senior consultants to support data analysis projects, with a focus on the banking and financial services sector.
• Assist in collecting, cleaning, and structuring data from diverse sources to prepare it for analysis.
• Identify trends, patterns, and key insights from data to address client business challenges.
• Develop reports, dashboards, and presentations to effectively communicate data insights to clients.
• Participate in client meetings to help translate complex technical findings into actionable, business-focused recommendations.
• Ensure data quality and accuracy by conducting thorough validation and integrity checks.
• Stay updated on industry trends, particularly in banking and data analytics, to provide cutting-edge solutions.
• Work closely with cross-functional teams to ensure project goals align with overall business objectives and client needs.
• Create and maintain dashboards and reports to monitor key performance indicators (KPIs).
• Present findings to stakeholders in a clear and concise manner, ensuring complex data is easily understood by non-technical clients.
• Perform regular data validation and quality checks to maintain high standards of accuracy and reliability.
• Contribute to process improvement by identifying opportunities to enhance data collection methods and analysis processes.