Functional & Ind Analytics Sr Analyst

Job description

Join Accenture Digital and leave your digital mark on the world, enhancing millions of lives through digital transformation. Where you can create the best customer experiences and be a catalyst for first-to-market digital products and solutions using machine-learning, AI, big data and analytics, cloud, mobility, robotics and the industrial internet of things. Your work will redefine the way entire industries work in every corner of the globe.

You'll be part of a team with incredible end-to-end digital transformation capabilities that shares your passion for digital technology and takes pride in making a tangible difference. If you want to contribute on an array of the biggest and most complex projects in the digital space, consider a career with Accenture Digital.

People in our Client and Market career track drive profitable growth by developing market-relevant insights to increase market share or create new markets. They progress through required promotion into market-facing roles that have a direct impact on sales.

Search & Content Analytics uses advanced techniques in Natural Language Processing & Understanding to enable comprehension of the vast amounts of our customers' unstructured text content. We build customized analytics platforms based on combinations of search engines, Big Data clusters, and machine learning in order to process that data, discovering trends and insights to help clients better understand their business, customers, and markets. From chatbots and question answering systems to cutting-edge user experiences like predictive need fulfillment, our group creates exciting improvements for everyone from end-users to data providers to boardroom decision-makers.

Please join as:

Functional and Industry Analytics Analyst

Engineers undertake activities on a project-by-project basis, either individually or as part of a larger team, and in projects that will vary in duration. They develop and customize search and analytics application software for specific client projects in a variety of markets. They provide onsite analysis and written assessments of existing customer installations with recommendations for improvements or upgrades. They participate in the analysis, design, and implementation of search and analytics applications. Travel (to client sites) as needed is to be expected.

Key Responsibilities of the role include:

Design/implement applications following specifications using tools that will vary depending on the project, including but not limited to the following:

·
Programming Languages: Java, C# (.NET), R, Python, Groovy, JavaScript

·
Frameworks: Maven, Spring, Struts, Hibernate, WebAPI, AngularJS, Node.js, RStudio, Jupyter

·
Technologies: JSON, SOAP, REST, Machine Learning algorithms (especially for regression & classification)

·
Security Protocols/Standards: Kerberos, LDAP

Desired profile

Qualifications :

Basic Qualifications

·  Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, Engineering or related.
·  Minimum of 2 years' experience in core software development environment(s)
·  Fluent English


Preferred Education & Experience

·  A Master's or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering or related.
·  Agile Methodologies Certification (e.g. CSM)
·  Basic knowledge of software project management practices
·  Knowledge of enterprise search platforms (Elasticsearch, Solr, Lucene, Endeca)
·  Experience in various statistical and machine learning models, data mining, unstructured data analytics in corporate or academic research environments
·  A minimum of 1 year of experience of hands-on experience in data science and statistical modeling.
·  A minimum of 1 year Experience using either one of the following (Python, R, Scala)
·  A minimum of 1 year experience writing production level code
·  A minimum of 1 year Experience with Machine Learning libraries such as scikit-learn, mlr, mllib
·  Industry experience in predictive modeling and data analysis
·  Experience with deep learning
·  Experience with AWS technologies such as Redshift, S3, EC2, EMR, etc.
·  Experience working with GPUs to develop models
·  Experience with large data sets and tools like Spark, MapReduce, Hadoop, Hive, etc.
·  Using Amazon ML services and platforms such as SageMaker, Rekognition, Comprehend, Lex, etc.