Customer Care Executive

Company Profile
XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with large data sets to find
opportunities for product and process optimization and using models to test the effectiveness of different courses of
action. They must have knowledge using a variety of data mining/data analysis methods, using a variety of data tools,
building, and implementing models, using/creating algorithms, and creating/running simulations. They must be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.

● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.

MUST have skills (not just a class room training experience please) –

1. Hands on experience on Postman/ SOAP UI/ REST ASSURED/JUnit framework for API testing
2. Hands on experience on GIT, JIRA, Jenkins
3. Good Understanding of REST API types (GET, PUT, POST, DELETE) an it’s working
4. Good understanding of HTTP, JSON protocol and syntax
5. Good understanding of Message Schema, RAML, Message Request-Response mechanism
6. Working experience in Agile methodology.
7. Strong written and verbal communication skills (English).
8. The candidate should be good with communication as he/she will be interacting with global teams very often.

GOOD to have –

1. Understanding of STUB/Service virtualization
2. Understanding of any API testing tools like –Rest Client, Anypoint etc.
3. Been able to understand Retail Banking functions/requirements.

 

Key Activities

 

• Primary responsibility for test automation within Agile delivery streams
• Experience with building test automation frameworks and Continued Integration
  • Some amount of manual exploratory testing
  • Test preparation, test design, execution and reporting
  • Defect management lifecycle exposure (using Jira) from defect reporting to tracking to closure
  • Writing test plans and test completion reports
  • Active in Agile meetings when required for planning, retrospectives

Abap Hana

• Configure IDOC settings relate to segment, IDOC type, message type, partner profile, port, RFC connection etc.
• Develop Java class for AES symmetric decryption and decompression of web service.
• Configure the EDI process to enable client to exchange documents with the business partners.
• Develop a program to update credit card details from a FTP file in FI/CO.
• Modify the above LSMW to accumulate quantity for the same records and post as one record.
• Develop a BDC for FICO to calculate and update full payment, partial payment and pending.
• Develop the data migration programs for vendor master and customer master upload from legacy system using LSMW.
• Embed the e-mail body content of customer in auto response e-mail generate by CRM system to the customer.
• Act on programs for credit card encryption/decryption to update and settlement in contract and billing in SD and FI/CO.
• Create report which will take data from SRM system against valid PO numbers and perform the calculations in ECC system.
• Configure asset module (fix assets), including asset classes, integration with purchasing, and assets under construction.
• Create picking list using message type PICKSD and corresponding IDOC type SDPIODO1 is used for sending information to warehouse management system.
• Develop a custom workflow for employee simplify performance management reviews and identification of top performers.
• Perform requirement gathering and technical feasibility over client expectation and defining development guidelines for ABAP team.
• Create technical specification for all the objects like workflow specification and report specifications base on the functional specification.

• Take the lead of scrum teams as the Product Owner
• Providing vision and direction to the Agile development team and stakeholders throughout the project and create requirements
• Ensure that the team always has an adequate amount of prior prepared tasks to work on
• Plan and prioritize product feature backlog and development for the product 
• Define product vision, roadmap, and growth opportunities 
• Assess value, develop cases, and prioritize stories, epics, and themes to ensure work focuses on those with maximum value that are aligned with product strategy
• Provide backlog management, iteration planning, and elaboration of the user stories 
• Work closely with Product Management to create and maintain a product backlog according to business value or ROI 
• Lead the planning product release plans and set the expectation for delivery of new functionalities 
• Provide an active role in mitigating impediments impacting successful team completion of Release/Sprint Goals 
• Research and analyze market, the users, and the roadmap for the product 
• Follow our competitors and the industry 
• Keep abreast with Agile/Scrum best practices and new trends

• Previous overall working experience of 8-14 years, including 3-5 years working as a Product Owner. 
• Bachelor’s in Engineering 
• In-depth knowledge of Agile process and principles 
• Outstanding communication, presentation, and leadership skills 
• Excellent organizational and time management skills 
• Sharp analytical and problem-solving skills 
• Creative thinker with a vision 
• Attention to details 

Responsibilities:

• Interact & Interview Chairperson of college or university.
• Featured & Research oriented articles about the Education System.
• Interview of famous personalities from the educational industry.
• Stories of success from leading professionals.

Requirements:

• Proven working experience as a Reporter.
• Portfolio of published articles.
• Computer proficiency (MS Office, digital editing, web search, databases)
• Excellent communication, lobbying, and active listening skills.
• Good hold in education industry persons.
• Bachelors degree in journalism or mass communications.