Your day at NTT DATA<\/p>\n
\tThe 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.\u00a0
\n\tThe 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.<\/p>\n
Key Responsibilities:<\/p>\n
\tDesigns, develops, and programs methods, processes, and systems to consolidate and analyze unstructured, diverse \u201cbig data\u201d sources to generate actionable insights and solutions for client services and product enhancement.
\n\tDesigns and enhances data collection procedures to include information that is relevant for building analytic systems.
\n\tAccountable for ensuring that data used for analysis is processed, cleaned and, integrally verified and build algorithms necessary to find meaningful answers.
\n\tDesigns and codes software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
\n\tAccountable 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.
\n\tAccountable for performing analysis using programming languages or statistical packages such as Python, Javascript, etc.
\n\tDesigns scalable and highly available applications leveraging the latest tools and technologies.
\n\tAccountable 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.
\n\tCreates SQL queries for the analysis of data and visualize the output of the models.
\n\tCreates documentation around processes and procedures and manages code reviews.
\n\tAccountable for ensuring that industry standards best practices are applied to development activities.<\/p>\n
Knowledge and Attributes:<\/p>\n
\tSeasoned in data modelling, statistical methods and machine learning techniques.
\n\tAbility to thrive in a dynamic, fast-paced environment.
\n\tQuantitative and qualitative analysis skills.
\n\tDesire to acquire more knowledge to keep up to speed with the ever-evolving field of data science.
\n\tCuriosity to sift through data to find answers and more insights.
\n\tGood understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face.
\n\tAbility to translate technical findings clearly and fluently to non-technical team business stakeholders to enable informed decision-making.
\n\tAbility to create a storyline around the data to make it easy to interpret and understand.
\n\tSelf-driven and able to work independently yet acts as a team player.
\n\tAble to apply data science principles through a business lens.
\n\tDesire to create strategies and solutions that challenge and expand the thinking of peers and business stakeholders.<\/p>\n
Academic Qualifications and Certifications:<\/p>\n
\tBachelor\u2019s degree or equivalent in Data Science, Business Analytics, Mathematics, Economics, Engineering, Computer Science or a related field.
\n\tRelevant programming certification preferred.<\/p>\n
Required experience:<\/p>\n
\tSeasoned experience in a data science position in a corporate environment and\/or related industry.
\n\tSeasoned experience in statistical modelling and data modelling, machine learning, data mining, unstructured data analytics, natural language processing.
\n\tSeasoned experience in programming languages (Javascript, Python, etc.).
\n\tSeasoned experience working with and creating data architectures.
\n\tSeasoned experience with extracting, cleaning, and transforming data and working with data owners to understand the data.
\n\tSeasoned experience visualizing and\/or presenting data for stakeholder use and reuse across the business<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
<\/p>\n","protected":false},"author":2,"featured_media":0,"template":"","meta":{"_promoted":"","_job_location":"","_application":"","_company_name":"NTT Ltd.","_company_website":"","_company_tagline":"","_company_twitter":"","_company_video":"","_filled":0,"_featured":0,"_remote_position":0,"_job_salary":"","_job_salary_currency":"","_job_salary_unit":""},"job_listing_region":[11],"job-types":[34],"class_list":{"0":"post-15329","1":"job_listing","2":"type-job_listing","3":"status-expired","4":"hentry","5":"job_listing_region-gauteng","7":"job-type-full-time-hybrid"},"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/job-listings\/15329","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/job-listings"}],"about":[{"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/types\/job_listing"}],"author":[{"embeddable":true,"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/users\/2"}],"wp:attachment":[{"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/media?parent=15329"}],"wp:term":[{"taxonomy":"job_listing_region","embeddable":true,"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/job_listing_region?post=15329"},{"taxonomy":"job_listing_type","embeddable":true,"href":"https:\/\/jobs.dataaxisnode.com\/southafrica\/wp-json\/wp\/v2\/job-types?post=15329"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}