HR - Talent Acquisition at Pioneer Financial & Management Services Ltd
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Solution Architect - Big Data - BFSI/Telecom/Manufacturing/Cloud Domain - IT Service Firm (10-18 yrs)
The Solution Architect will work closely with Banking and Financial Services customers to translate their data management and analytics requirements into a solution which meets industry standards. The architect should have experience in interacting with the customer to understand their requirements, discuss possible options of architect solutions, design of the architecture, identify the right applications and services, define best practices for the execution of the solution, testing and deployment. He should be capable of understanding the complexity of the data in terms of variety, volume, and velocity and recommend appropriate design patterns for the varieties of data being handled.
He should have independently worked on proposing an architecture, design, and data ingestion concepts in a consultative mode and participated in presenting the solution to the customer CXOs and Data Offices. He should also have lead consulting engagements in the nature of assessment studies, roadmap and strategy definition. Should be a team player and work with vertical leaders as well as competency leaders for identifying opportunities and pro-actively pitch the Data & Analytics offerings.
Required Skills -
- Must have minimum 5+ years hands-on experience in one of the Big Data Technologies (I.e. Apache Hadoop, HDP, Cloudera, MapR)
- 3+ years of demonstrable experience designing ML/statistical solutions/Big Data to complex business problems at scale
- Focus on building Banking and Financial Services industry grade solutions to address industry-specific challenges
- Fluent with digital areas related to data & analytics: Digital Technology - Mobility, Cloud, Analytics, Big Data, etc.
- Develop & code production-grade novel algorithms for our business-experimentation platform
- Experience Involves testing various machine learning and analytical tools, especially in the big data space, to scale prototypes to production-grade systems.
- Provide solutions but not limited to: Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization
- Proficient in statistical/ML predictive techniques such as regression, Bayesian methods, tree-based learners, SVM etc
- Proficiency in at least one of R or Pythons (preferred) data science stack
- A good learner, a good mentor, who inspires peers and team members to learn and expand their skill set, guiding them in the right direction.
- Working knowledge of MapReduce, HBase, Pig, MongoDB, Cassandra, Impala, Oozie, Mahout, Flume, Zookeeper/Sqoop and Hive
- Technical competencies in the space of Business Intelligence and Database
- Exposure to data and analytics technologies on various cloud providers like AZURE, GCP, and AWS
- Should be well versed with agile methodologies, DevOps.
- Thorough grasp on RDBMS and data management concepts as well as fluency in SQL scripting
- Good customer presentation and communication skills
- Should be passionate about Data & Analytics technologies and trends in the market
- Should be conversant with the current trends in the Banking, Financial Services, and Insurance Vertical
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