Big Data Consultant
Description
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
The Tiger Analytics team is looking for an Analytics Consultant (Business Analytics) to support the project management activities and provide business intelligence, data analytics, metrics, and reporting. The candidate will translate policy and strategic initiatives to quantitative data analysis and investigative data research. The Analytics Consultant (Business Analytics) will discuss key business objectives with stakeholders, build internal analytics modeling IP and accelerators, and provide insight into what business users are looking for and would these business initiatives prove profitable.
Job Duties
- Develop Big Data analytics frameworks and solutions for business problems by customizing preexisting internal data and analytics platforms and tools
- Examine existing data architecture for client’s big data platforms and then monitor, collect, and review business requirements, and related technology solutions
- Suggest designs for new big data frameworks and Data Lake solutions and establish platform governance via data-flow-diagrams, and system reviews for all new initiatives and existing programs
- Solve problems of large dimensionality (terabytes of data storage) in a computationally efficient and statistically effective manner
- Collaborate with technical teams to advance emerging platform features for artificial intelligence, machine learning, advance analytics, cloud data warehousing, and metadata management
- Create data pipelines so data can be used for the purposes of Data Science, Machine Learning, Artificial Intelligence, Operational Research techniques
- Apply Machine Learning, Deep Learning, simulation and Al processes in an Agile development framework to advance personalization, real time decision making, causal inference, and predictive analytics capabilities
- Survey business users and IT teams to collect and document data sets that can be used to drive business insights, and then analyze the same data sets provided to determine the business problems. Test the solution algorithms created and build a testing framework that can yield repeatable testing strategies for measuring results produced by analytics models
- Research best academic and industrial practices in the Big Data Analytics field and use this knowledge to advise clients on the latest tools and technologies in the field
- Oversee end-to-end analytical solutions using Big data architectures, including identifying parts of a data driven business that require Big Data solutions, developing and discussing a proposal with client’s cross-functional teams, dividing project goals into specific tasks, working with client’s IT stakeholders to deliver the solution, collect and validate all data, and evaluate said data for consistency and accuracy
Requirements
- A bachelor’s degree in Computer Science/CIS or closely related field
- 3 – 5 years of experience with identifying parts of a data driven business problem that require Big Data solutions, developing flow charts and solution diagrams proposal, and discussing the proposal with client’s teams to divide project goals into specific tasks involving business analysis, data analysis and data engineering
- Proficient in building large scale fault tolerant enterprise applications using Hadoop and Big Data open source solutions such as: MR, Hive, Pig, HBase, Spark
- Proficient with solving problems of large dimensionality
- Experience with developing new data sources and stimulating market scenarios using Python, or other programming tools such as R, Hadoop, to create and evaluate new additions to enhance data assets.
- Extensively worked on data architecture and end to end data solutions that include SQL, Cassandra, Kafka, ActiveMQ, Elastic Search, HBase, Teradata and other. Experience with identifying improvement opportunities for the data ingestion process and developing repeatable testing strategies for measuring results produced by analytics models
- Lead teams of Data Engineers and Analyst and benchmark the developed solution for data consistency, data latency, data quality and deployment.
Please send your resumes to [email protected]
