Experience : 6-10 years
Summary of Job Purpose :
A revolution is brewing, and Absolutdata is the epicentre of the revolution called Big Data - A megatrend impacting every facet of business decision making.
With our extensive experience converting big data into big insights, client are reaping large bottom-line and top-line results.
Be it large amounts of data (Volume), fast changing or streaming data (Velocity) or multiple types of data such as unstructured data (Variety), traditional analytics is combined with emerging analytics such as Machine Learning and Artificial Intelligence to connect data with business results.
In making this connection, technology plays a huge role. This is where the Products Team at Absolutdata comes in. A team that combines Data, Analytics and technology together to deliver business results.
Over the last few years, Absolutdata, a global leader in Analytics and Big Data Services, has launched its Marketing and Sales domain focused, AI & ML powered, decision engineering suite called NAVIK AI.
In their suite currently there are 3 products NAVIK MarketingAI, NAVIK SalesAI and NAVIK MR AI and an AI platform. As a core part of the strategy for the firm, Absolutdata has ambitious plans to develop the platform and these three products furthers as well are add several more products within the NAVIK AI suite.
This is where the products team at Absolutdata comes in. A team that combines Data Science and Technology together to deliver business results.
The role is a mix of data science, product management and client management. The person primary responsibilities would be the following :
Job Description :
Exposure to open source analytical tools such as R, Python, KnimeUnderstanding of data visualization & experience with tools such as Tableau, R Shiny, QlikView, etc (any one).
Software engineering practices for the full software development life cycle, including coding standards, code reviews, unit testing, TDD, source control management, continuous integration, defect management, build processes & testing
Some exposure to cloud and it’s components AWS / Azure / Google Cloud Platform (any one)Knowledge of ETL methods such as data imputation, data cleaning, outlier handling, etc.
Knowledge of databases and associated tools e.g. RDBMS, SQL, etc.
Management of small team of data scientists and engineers
Preferred Experience :
Specific Responsibilities :