Job Description

At NTT we believe that by using innovative technology we can solve global challenges and create a world that is sustainable and secure. We are looking for curious people, from diverse backgrounds, that are keen to work in a fast-paced and agile environment.

At NTT we trust our employees to do the right thing, even when no one is watching, which is why we offer flexibility in the workplace. The majority of our roles are hybrid, meaning we encourage a balance of working from home and our local office. Ask our recruitment team if this is a hybrid role.

Want to be a part of our team?

Designs, develops, and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.

Interacts with product and service teams to identify questions and issues for data analysis and experiments.

Develops and codes software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.

Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

Working at NTT

Data Scientists apply and inspire the adoption of data science and analytics across the NTT organization.

The primary responsibility of this job is to create and deliver data-driven solutions that add business value using statistical models, machine learning algorithms, data mining, and visualization techniques.

Key Roles and Responsibilities:

• Collaborate with business stakeholders to identify opportunities for leveraging data to drive business solutions
• Research, design, implement and deploy scalable data analytics vision and machine learning solutions to challenge complex business issues
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis, and building algorithms necessary to find meaningful answers
• Perform analysis using programming languages or statistical packages such as Python and R etc.
• Mine and analyze data to drive optimization and improvement of business strategy
• Architect scalable and highly available applications leveraging the latest tools and technologies
• Creatively visualize and effectively communicate results of data analysis, insights, and ideas in a variety of formats to key decision-makers within the business
• Take ideas to successful launch by leading and mentoring diverse, geo-distributed teams through innovation, bootstrapping, pilot, production, scaling, and maintenance phases with multiple stakeholders to the highest levels of quality and performance
• Develop SQL Queries for reports and dashboards
• Analyze relational and transactional databases to provide data analysis, and present results in a clear manner
• Create documentation around processes and procedures and manage code reviews
• Apply industry standards best practices to development activities
• Work on data set to ensure solutions are successfully executed, within agreed upon time frames

Knowledge, Skills, and Attributes:

• Subject matter expertise in data modeling
• Theoretical understanding of statistical methods and machine learning techniques
• Ability to thrive in a dynamic, fast-paced environment
• Excellent quantitative and qualitative analysis skills
• Strong desire to acquire more knowledge in order to keep up to speed with the ever-evolving field of data science
• Strong curiosity to sift through data to find answers and more insights
• Solid understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face
• Ability to clearly and fluently translate technical findings to non-technical team business stakeholders to enable informed decision-making
• Ability to create a storyline around the data to make it easy to interpret and understand
• Theoretical understanding of statistical methods and machine learning techniques
• Self-driven and able to work independently, yet acts as a team player
• Able to apply data science principles through a business lens
• Strong desire to create strategies and solutions that challenge and expand the thinking of everyone around you
• Ability to think strategically about how to use data to drive competitive advantages

Academic Qualifications and Certifications:

• Degree in Data Science, Business Analytics, Mathematics, Economics, Statistics, Engineering, Computer Science, Computer Engineering or another quantitative field (preferably a bachelor’s degree or equivalent)
• Relevant programming qualifications and/or certifications
• Relevant Agile certification is preferable

Required Experience:

• Demonstrable experience with one or more programming languages (e.g. Python), statistical packages (e.g. R), and database languages (e.g. SQL)
• Demonstrable experience with data warehouse and data lake technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. (excellence in at least one of these is highly desirable)
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc
• Demonstrable experience in data modeling
• Demonstrable experience applying statistical methods and machine learning techniques to solve business problems
• Experience with distributed data/computing tools such as Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.
• Experience in working in micro-services architecture working with APIs development
• Demonstrable experience of full-stack software development with prolific coding abilities
• Demonstrable experience in Elastic search, Scoring, and recommendation on very large volumes of data
• Experience with Agile Development Methodologies and Test-Driven Development

What will make you a good fit for the role?

• 2-3 years experience.
• Tertiary qualifications (a Masters or PhD degree) in a quantitative discipline, such as Statistics, Econometrics, Applied Mathematics, Engineering, Applied Science., or equivalent highly desired.
• At least one of the following modelling software packages: MATLAB, R, SAS, SPSS.
• At least one of the following scripting languages: C++, Java, Python.
• Data visualisation using Tableau / Qlikview / D3.js
• Demonstrating your ability to adapt quickly and manage an environment of rapid change and development, and lead others through this process

Join our growing global team and accelerate your career with us. Apply today.

Equal opportunity employer

NTT is proud to be an equal opportunity employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, color, sex, religion, national origin, disability, pregnancy, marital status, sexual orientation, gender reassignment, veteran status, or other protected category.