As a Data Scientist at IBM, you will help transform our clients’ data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.
Your Role and Responsibilities
As businesses, governments and communities become more data driven in their decision making and business operations, demand on the new and innovative data related capabilities are exponentially growing. As trusted advisor to the Chief Data Officer, CIO and Head of Data Program in the enterprises, build compelling value proposition for flexible and futuristic data architecture on enterprise and open source tools. You will define the migration strategy of client’s data & ai workloads to the cloud of IBM and non IBM providers. You will partner with sector teams, global markets team and all IBM brands to sense, originate, qualify opportunities, and pursue the deals to closure.
- Work closely with the deal teams to shape and solution data programs, continuously engage with key client executives and share IBM solution details, effectively communicate value proposition on the new age big data, data on the cloud stack to help modernize client’s data program.
- Own end to end delivery of, a) large & complex data transformation programs, b) small and nimble data initiatives to realize quick gains, c) work with IBM and Partners to bring the best tools and delivery methods.
- Own the offerings and assets on key components of data supply chain, data governance & curation, data quality and master data management, data integration, data replication, data virtualization, self service interaction for data preparation and testing
- Build key partnerships with top tools, platform and cloud providers.
- Improvise new and innovative data assets and drive it’s adoption to the market.
- Be a thought leader on data supply chain
- Apply knowledge and explain the benefits gained by organizations implementing strategies relating to: Big Data (incorporating Hadoop, and analytics), Business Continuity, Disaster Recovery, Cloud implementation, and DevOps. Ability to identify product, utilities, and tools commonly used in relation to the topics above.
- Worked in building core data assets of one of the cloud providers
- Familiarity of new and emerging technologies like Edge Computing, with data & workload processing on cloud, edge and devices
- Relationships with various technology providers (e.g. ETL, DV, Data Lake, Reporting and Visualization, API management, Security etc) to build end to end solution satisfying client needs and successful project delivery
- Strong relations in the Indian market with key client decision makers
Required Technical and Professional Expertise
- Someone who has traversed the data journey, having moved the clients through the modernization of data warehouse to data lakes to data operations on the cloud.
- Worked in a third party consulting, service, technology organization for a fair share of the career.
- Consulted clients on aspiration to make them information led decision making business.
- Hands on expertise in building and implementing data architecture for large enterprises.
- Proven deep client relationships and drive the advisory agenda.
- Proven ability to enhance value of an opportunity through new technology
- Ability to run multiple and disparate client conversations, opportunity pursuits, and handle the execution of dynamic practice agenda.
- Should have hired and nurtured talent and grow them in market facing specialists and consultants. Should have built a community of practice on data.
Preferred Technical and Professional Expertise
- Support both the development of new business opportunities and the delivery of data platform services to clients.
- Deep expertise in applying Analytics for two or more industries (BFSI, Manufacturing, Distribution, Electronics, Oil&Gas etc.)
- Advise clients in the planning, design, management, execution, and reporting of the core components for big data offerings. Skills include: architecture, tool selection, data lake design and implementation
- Advise on Big Data design across multiple platforms with extensive experience on very large data repositories. Skills include: HADOOP Framework, Ecosystem and MapReduce.
- Experience with one or more of these skills: HDFS, Spark, PySpark, HBase, HIVE, PIG, Solr, Java/C++, SQL, Linux, other large scale data technologies