What you’ll do:

• Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule
• Software Development that creates data driven intelligence in the products which deals with Big Data backends
• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements
• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development
• Managing, data in large scale data stores (such as NoSQL DBs, time series DBs, Geospatial DBs etc.)
• Creating metrics and evaluation of algorithm for better accuracy and recall
• Ensuring efficient access and usage of data through the means of indexing, clustering etc.
• Collaborate with engineering and product development teams

What makes you a great fit:

• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school or master’s degree or higher in Statistics, Mathematics, with hands on background in software development.
• 8 to 10 years of experience in product development, having done algorithmic work
• 5+ years of experience working with large data sets or do large scale quantitative analysis
• Understanding of SaaS based products and services.
• Strong algorithmic problem-solving skills
• Able to mentor and manage team and take responsibilities of team deadlines
• In depth Knowledge Python programming languages
• Understanding of software architecture and software design
• Must have fully managed a project with a team
• Having worked with Agile project management practices
• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)
• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis)
• Understanding of working and managing large Databases such as indexing, sharding, Caching etc.
• Knowledge of Big Data technologies such as Hadoop, Yarn, Redshift, Spark, Kafka, Pig/Hive etc.
• Understanding of Machine learning algorithms
• Understanding of geospatial data stores, PostGIS will be a plus.
• Exposure to Data visualization desirable