Objective to manage Data collection, consolidation, correlation, classification, labeling, mining, predictive modeling, clustering of different Data sources within the company, Partners, sensors and public domain into company Data Lake, in order to analyze raw data to discern a set of rules and the factors influencing those rules to achieve organizational goals; Use algorithms and programming to efficiently apply treatments, filters & conditions to data from large datasets (structured & unstructured data).
Assemble large, complex data sets that meet functional / non-functional business requirements.
Performing Data Services, Machine Learning modeling, Deep Learning algorithms, Bot Trainings and Neuronal Training in relation to Business Decisions, Actions and Visualization such as, improving customer experience, enhance products and maintain customer satisfaction at highest.
Design, Develop and Maintain fault tolerant and future proof data infrastructure for Og Products for analytics and advanced analytics purpose.
Pave the path to build Intelligent machines, virtual assistants and personal conversational assistants with historical and behavioral knowledge to fully handle customer inquiries, predict and manage human alike conversation assistance from problem solution to Service transaction through text and natural language / voice dialog on web and Apps.
Design, Develop and Maintain Big Data Infrastructure (Data Warehouse, Mart & Automated Pipelines).
Develop and Maintain BI Reports and Dashboards publish via data visualization and dashboard.
Identify and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Azure and AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Keep our data separated and secure across national boundaries through multiple sources and Cloud.
Optimize algorithm performance such that we can efficiently process large datasets and equivalent 10MB images at 10 FPS on edge devices.
Develop high-performance and highly parallel software kernel implementations for GPUs together with the math library and ML team.
Implement machine learning frameworks for automatically retraining models, generating accuracy metrics, and deploying models to production.
Screening Criteria:
Immediate joiners
Min 3 to 5 years of Experience
location: Remote
Qualifications:
Bachelor's degree in Computer Science, Engineering, or a related field.
Primary skills (Must have):
Machine learning and deep learning.
Sound knowledge in AI.
Dash and plotly, power bi, Qlickview, airflow, Postgres , mssql and Hive, HDFS , hive , sqoop , zeppline, spark, Sqoop, oozie & Spark.
DATA SERVICES SKILLS:Python and R programming Languages,Data analysis, statistical analysis.
MACHINE LEARNING SKILLS:Computational Statistics,Mathematical Optimization,Exploratory Data Analytics,Predictive Model Development.
DEEP LEARN DATA SCIENTIST SKILLS:Object Detection,Segmentation,Classification,Re-Identification with other Computer Vision Tasks.
Programming languages, such as SQL, and Python.
Experience with a variety of database technologies such as MySQL, MongoDB, and HADOOP, CASSANDRA operating in large scale environments.
Write scripts and utilities to monitor, manage, and maintain databases. Experience with scripting; PHP, python, JavaScript or bash programming.
Experience with data access layer APIs.
Experience with Database Engineering or Database Administration, preferably in a WINDOWS or Linux environment.
