- 2-7 years of hands on work experience in NLP, AI, Machine Learning, Deep Learning
- BE/BTech, MTech, MSc. in Computer science/Information Technology/ ECE or other quantitative disciplines from tier 1/ tier 2 institutes
- Strong foundation and hands-on experience in NLP and Machine Learning
- Should have developed and deployed NLP based solutions with R( tm, korPus, etc) or Python( NLTK, Scikit-learn and Spacy
- Strong familiarity with Deep Learning methods for text analytics is highly desired – RNN, LSTM, word2vec and other embeddings, Keras/Tensor flow.
- Knowledge of Chabot platforms and development and deployment of at least 1 NLP based Chatbot or other AI, machine learning, or NLP technologies
- Strong background with advanced mathematical concepts and understanding of algorithms
- Working with Speech to Text and conversational analysis tools /Api, such as Dialogflow is a plus
- Working knowledge of Image matching, and understanding applications of voice and video data is a plus
- Experience in working with cloud infrastructure and high-performance computing (GPU/TPU) be a plus
As a QlikView/Qlik Sense Developer will work in a client-facing role to design and develop QlikView/Qlik Sense data models and dashboards to support our client needs. The role requires complete comprehension of enterprise data models and utilization of both relational and dimensional data sources. The ideal candidate will have experience in QlikView/Qlik Sense design and development with a general understanding of BI and reporting.
- Perform detailed analysis of source systems and source system data and model that data in QlikView/Qliksense
- Design, develop, and test QlikView/Qliksense scripts to import data from source systems and test QlikView/Qliksense dashboards to meet customer requirements
- Interpret written business requirements and technical specification documents
- Create and maintain technical design documentation
- Perform quality coding to business and technical specifications
- Insure that the QlikView/Qliksense server process continues to run and operate in the most efficient manner
- Perform QlikView/Qliksense system administration and testing of releases and patches
- Work directly with business units to define and prototype QlikView/Qliksense Applications
- Extracting, transforming and loading data from multiple sources into QlikView/Qliksense applications
Desired Skills and Experience:
- Experience in developing / architecting BI Solutions supporting in Retail, Financial, sales, and supply chain performance reporting.
- Experience in sourcing data from disparate systems with a good understanding of their Data Models and ETL procedures
- Hands-on professional with thorough knowledge of scripting, data source integration and advanced GUI development in QlikView/Qliksense
- Full understanding of the processes of data quality, data cleansing and data transformation
- Ability to write complicated yet efficient SQL queries and stored procedures
- Strong knowledge on QlikView server architecture. Qlik Sense Server Architecture, handling changes in QMC and building qvd’s and qvw’s applying business rules and data validations.
- Experience in Full Cycle end-to-end implementation of Business Intelligence (BI) projects, especially in scorecards, KPIs, reports & dashboards
- Knowledge of formal database architecture and design
- Experience as a consultant in a client-facing role for a top tier or similar consulting organization is highly desirable
- A bachelor’s degree in computer science, information technology, information systems, or a related discipline
We have Job Opportunity with one of our esteemed clients who is into Banking Sector. Please find the Job details below:
- Looking for Candidates who have experience in the domain of Big Data/Machine Learning from statistics & Analytics domain.
- Experience in Analyzing the Medium Complex Problems and translate it into Analytical Approach
- Experience in Statistical Learning : Diagnostic Analytics, Simulation and Predictive Modeling,, Time Series, Dynamic/Causal Model, Statistical Learning, Guided Decisions
- Lead role mentoring Jr. Analysts on approach and results.
- Experience with big data analytics and advanced data mining techniques to analyze data
- Experience with identifying trends, patterns, and outliers in data
- Experience with statistical programming languages using analytical Packages/library :- R, Python
- Experience with statistical Tools (R studio, Revolution R, Win Python)
- Experience with SQL and relational databases, data warehouse
- Experience with big data platforms – Hadoop(Hive, Pig, Map Reduce, HQL)
- Experience with statistical programming languages – SAS
- Experience with statistical Tools (For ex: SAS EG, Enterprise Miner, Text Miner, KXEN, OPL/CPLEX, SPSS,R studio, Revolution R)
- Experience with data warehouse platforms – Teradata / Green Plum, HANA
- Bachelor’s / Master’s in Computer science Engineering OR Masters in Statistics/Mathematics
- Data Scientist people also will be considered.
What role you play:
- Designing and developing Machine Learning use cases using appropriate ML Algorithms and Tools
- Transform Business Requirements to working real life applications with Machine Learning modules and use cases
- Understand the Data and perform Feature Engineering and develop Machine Learning use cases
- Create prototypes of ML Use Cases and present to Customers and other relevant stakeholders
- Participate in Software Development life-cycle to productize the Machine Learning use cases
- Keeping abreast of developments in the field of ML and AI. Helping in Training and Coaching others in the organization
Programming and software skills
- Python Programming for ML (Python for Data Science and ML)
- R Language
- Core Java programming
- Data stream processing (Kafka and Spark Streaming etc)
- Big Data processing (Spark and databases – SQL and NOSQL)
- Data Engineering skills
- Work with large amount of real Data
- ML Frameworks, Tools and Environment
- Apache Spark and Spark ML
- Microsoft Azure ML Studio
- Python programming environment (Visual Studio, Jupyter Notebook/Lab, Anaconda etc)
- Basic view on the hardware and compute environment to run ML Use Case (use of GPU etc)
- Software Engineering
- Understanding of Software Development life-cycle process
- Agile, Scrum, Kanban Methodologies
- Ability to have a view on how ML Use Cases can be incorporated into Software Products
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