Do you love a challenge?
- Anyone can build an application which can process tens or hundreds of fields in a well-defined static manner. However, we deal with thousands of data points- which are stitched together to create a Knowledge Graph, in order to arrive at a comprehensive profile capturing diverse aspects like demographics, structural, behavioral, financial, legal etc.;
- On top of that, every day additional data points are added to this already massive pool of data sets. So, we intend to manage and process thousands of data points in a manner where the workflows can be auto-discovered basis the specified data points and the associated optimization objectives- everything in real time; Further,
the events like addition of new data points to Karza's datalake or the source slowdown/failures etc.
- Should be continuously monitored in the hope of discovering previously unknown workflows or optimizing/correcting the existing workflows. Also, depending upon the cardinality of the data point, different workflows/paths might have different workloads.
- This position will require designing and implementing various graph-based algorithms-which should be tunable in a declarative manner by our domain experts- without compromising on scalability, availability and performance.
Required Skills :
1. Extremely good in data structures and graph-based algorithms. Should be a fan of recursion and dynamic programming.
2. Should have worked on distributed processing frameworks like Spark/MapReduce/Cassandra/Elastic Search etc.
3. Should have a good conceptual understanding of rule-based engines & graph databases.
4. Should be aware of fundamental concepts in the field of information retrieval, graph mining, knowledge representation - ontologies etc.
5. Should be able to comprehend abstract problem statements and shouldn't refrain from reading research papers.
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