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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.
● Generate loan leads from the partnered institutions, open market and through different channels on the field.
● Develop and maintain relationships with partnered institutions and repeat business
and referral/s.
● Arrange and plan events to generate leads, and handle product queries and
service issues in the partnered institutions.
● Meet clients, verify documents, process files, coordinate for sanction /
disbursement of loans, personalized service to clients.
● Ensure the achievement of a given business target in your territory.
Experience: 1year+ in Banking sales such as personal loans, and home loans.
JD –
Having experience in Implementing Integration Solutions using Oracle Integration Cloud Service.
Developed integration between SaaS application (Oracle Cloud ERP, Oracle Cloud HCM) and between SaaS and PaaS application
Should have worked extensively on minimum 3-4 Technology Adapters like File, Database, Oracle ERP & FTP adapter
Should have excellent skill in Web Service technologies such as XML, XPath, XSLT, SOAP, WSDL, and XSD
Experience in all phases of software development lifecycle from gathering requirements to documentation, testing, implementation and support Ability to troubleshoot technical and configuration issues
Should be able to communicate effectively with the functional & technical groups and various technical team members.
Ensure completion of tasks, milestones, and components including Technical specifications, design specifications, configurations, quality assurance, implementations, and project reviews
- Must have 4 to 7 years of experience in ETL Design and Development using Informatica Components.
- Should have extensive knowledge in Unix shell scripting.
- Understanding of DW principles (Fact, Dimension tables, Dimensional Modelling and Data warehousing concepts).
- Research, development, document and modification of ETL processes as per data architecture and modeling requirements.
- Ensure appropriate documentation for all new development and modifications of the ETL processes and jobs.
- Should be good in writing complex SQL queries.
- • Selected candidates will be provided training opportunities on one or more of following: Google Cloud, AWS, DevOps Tools, Big Data technologies like Hadoop, Pig, Hive, Spark, Sqoop, Flume and
- Kafka would get chance to be part of the enterprise-grade implementation of Cloud and Big Data systems
- Will play an active role in setting up the Modern data platform based on Cloud and Big Data
- Would be part of teams with rich experience in various aspects of distributed systems and computing.
Very good knowledge of material design components
Angular CLI and CDK.
Creating new Components
String Interpolation and property binding.
In depth knowledge on angular Core package
Two way binding concept
Use cases on Angular Life cycle methods
Inbuilt directives and custom directive
Creation of Custom events and Event binding between components.
Communication between two custom components
Local references and View child and Content Child options
Services and Dependency Injection and its implementation in various use cases
Angular Routers and routing
Observables and their use and implementation
Pipes to transform output Creating Http request ( API handling)Dynamic Components
Good Knowledge of HTML5, CSS3, JQuery, Typescript
Proficient understanding of code versioning tools, such as Git, SVN
Adhering to best design practice
Good Written and Verbal communications.
We are looking to working with self-driven graduates who are looking for an opportunity to grow in the fields of search engine marketing, paid sales, PPC bidding and other performance-driven channels that make up a crucial chunk in digital marketing setup for business.
- Gain a thorough understanding of online marketing channels, everyday operations and processes of marketplaces like Amazon and Flipkart.
- Complete the analysis check list of the accounts to understand the market and its trends.
- Understand business requirements, perform and generate reports for PPC, daily account management of pay per click accounts on Amazon.
- Assist in the monitoring and maintenance of bids, quality score, account daily and monthly budget caps and other important metrics.
- Proactively make strategic PPC campaign recommendations.
- Understand client’s Amazon account performance in the management of Sponsored Product placements on all Amazon marketplace platforms.
- Support the generation of new PPC campaigns, ad, ad groups and accounts and in the aid of creating new paid search advertising initiatives.
- Provide recommendations and execute strategies for display network, campaign structuring, targeting, keyword opportunities, and other facets of paid search in accordance with client goals
- Keep pace with PPC industry, client domain market, search engine trends and developments.
- Work closely with the other team members on advertising to meet client goals.
- Communication to team and management on account performance, timelines, and results.
- Generate daily, weekly and monthly client reporting for all those major metrics such as revenue tracking, goals tracking, and other paid search initiatives
Role:-
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3. Data logging and sensor interfacing.
4. IOT gateway interfacing.