Machine Learning Engineer at NTT Ltd.

Your day at NTT DATA

• The Machine Learning Engineer (ML Engineer) is a subject matter expert, tasked with participating in the adoption of deploying machine learning models, data science and analytics within the organization. 
• The primary responsibility of this role is to participate in the creation and delivery of data-driven solutions that add business value using statistical models, machine learning algorithms, data mining, and visualization techniques.

Key Responsibilities:

• 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.
• Designs and enhances data collection procedures to include information that is relevant for building analytic systems.
• Accountable for ensuring that data used for analysis is processed, cleaned and, integrally verified and build algorithms necessary to find meaningful answers.
• Designs and codes software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
• Accountable for providing meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
• Accountable for performing analysis using programming languages or statistical packages such as Python, Javascript, etc.
• Designs scalable and highly available applications leveraging the latest tools and technologies.
• Accountable for creatively visualizing and effectively communicating results of data analysis, insights, and ideas in a variety of formats to key decision-makers within the business.
• Creates SQL queries for the analysis of data and visualize the output of the models.
• Creates documentation around processes and procedures and manages code reviews.
• Accountable for ensuring that industry standards best practices are applied to development activities.

Knowledge and Attributes:

• Seasoned in data modelling, statistical methods and machine learning techniques.
• Ability to thrive in a dynamic, fast-paced environment.
• Quantitative and qualitative analysis skills.
• Desire to acquire more knowledge to keep up to speed with the ever-evolving field of data science.
• Curiosity to sift through data to find answers and more insights.
• Good understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face.
• Ability to translate technical findings clearly and fluently 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.
• Self-driven and able to work independently yet acts as a team player.
• Able to apply data science principles through a business lens.
• Desire to create strategies and solutions that challenge and expand the thinking of peers and business stakeholders.

Academic Qualifications and Certifications:

• Bachelor’s degree or equivalent in Data Science, Business Analytics, Mathematics, Economics, Engineering, Computer Science or a related field.
• Relevant programming certification preferred.

Required experience:

• Seasoned experience in a data science position in a corporate environment and/or related industry.
• Seasoned experience in statistical modelling and data modelling, machine learning, data mining, unstructured data analytics, natural language processing.
• Seasoned experience in programming languages (Javascript, Python, etc.).
• Seasoned experience working with and creating data architectures.
• Seasoned experience with extracting, cleaning, and transforming data and working with data owners to understand the data.
• Seasoned experience visualizing and/or presenting data for stakeholder use and reuse across the business