Special projects
holistic spiritual
wellness platform using our Indian values
2 - 6 yrs
₹8L - ₹14L / yr
Bengaluru (Bangalore)
Skills
Management consulting
Project Management
Business Analysis
strategy
Closely work with the CEO and the Head of Strategy to own and drive various initiatives across
the organization (and externally)
● Use data and on-ground information to clearly identify the real problems beyond the
symptoms
● Break the problems into small and actionable units to ensure success
● Ideate and come up with different possible solutions and propose the most optimal one.
● Divide the solution proposed into multiple projects. Prioritize projects on the basis of impact
and effort required. Break down the projects further into actionable steps.
● Define the approach for all the actionable steps. Build the required processes with a focus on
accuracy, efficiency and scalability. Define and set up KPIs and success metrics to monitor the
health of the project. Prepare implementation guidelines and SOPs. Identify resources to work
with. Ensure the training of personnel involved and identify specific/periodic training programs,
the organization (and externally)
● Use data and on-ground information to clearly identify the real problems beyond the
symptoms
● Break the problems into small and actionable units to ensure success
● Ideate and come up with different possible solutions and propose the most optimal one.
● Divide the solution proposed into multiple projects. Prioritize projects on the basis of impact
and effort required. Break down the projects further into actionable steps.
● Define the approach for all the actionable steps. Build the required processes with a focus on
accuracy, efficiency and scalability. Define and set up KPIs and success metrics to monitor the
health of the project. Prepare implementation guidelines and SOPs. Identify resources to work
with. Ensure the training of personnel involved and identify specific/periodic training programs,
Read more
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Full Stack Developer - AverlonI had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
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production.
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Opportunities for application:
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- Promise Recommendation Engine etc.
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- 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
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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
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opportunities for product and process optimization and using models to test the effectiveness of different courses of
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comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
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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
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● 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.
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.
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Here is a chance to work for a Consumer Electronics Brand, where you get to deal with some of the best channels and work with some excellent experienced minds. Read on.
Started in 2015, this lifestyle and accessories startup has taken over the consumer electronics sector in India. Our client has a product range that includes an extensive catalog of headphones, speakers, travel accessories, and modern earphones. It believes in providing cutting edge electronic products stamped with durability and affordability.
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Started in 2015, this lifestyle and accessories startup has taken over the consumer electronics sector in India. Our client has a product range that includes an extensive catalog of headphones, speakers, travel accessories, and modern earphones. It believes in providing cutting edge electronic products stamped with durability and affordability.
The brand is associated with some of the major icons across categories and tie-ups with industries covering fashion, sports, and music, of course. The founders are Marketing grads, with vast experience in the consumer lifestyle products and other major brands. With their vigorous efforts toward quality and marketing, they have been able to strike a chord with major E-commerce brands and even consumers.
As a Component Sourcing Engineer, you will be responsible for the delivery, timely service and best-in-class Quality products and services to the Manufacturing Operations.
What you will do:
- Coordinating with Supplier Selection Process to develop a supply base that provides competitive advantage in quality, value/cost, delivery and technology.
- Undertaking business needs assessment, supply market analysis and commercial risk assessment to inform procurement planning and sourcing decisions
- Developing and administering contract management plans, negotiating changes and modifications, supplier performance management and compliance requirements through effective supplier relationships to enhance business outcomes
- Supporting to Identify, manage and mitigate procurement risks to enable the organisation to meet its obligations and maximize business opportunity
- Analysing all internal and external procurement information to effectively develop supply base strategies for major procurement projects.
- Identifying all suitable suppliers per commodity and region per sample RFQ and developing comprehensive supplier knowledge & database.
- Analysing and awarding best bid based on Total Cost of Ownership (TCO) approach.
What you need to have:
- Preferred Work experience in Wearables, Voice Tech Products, IoT
- Tier 1 Background preferred.
- Having experience in Sourcing, Vendor Development, Purchase
- Handled Electronic components, PCB, Mechanical Parts
- Experience with BOM, Costed BOM, Chinese Collaboration
- Should have strong knowledge in Selecting Alternate Components
- Should able to get or suggest best low-cost components
- Should have worked on Value engineering
- Knowledge about Import, Export, Costing, Projects
Read more
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Client Management
Customer Relationship Management (CRM)
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+1 more
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- SPOC for any conflict resolution
- Leads Account reviews
- Writes creative briefs, and approves payments to and from the client
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- Computer assembling and dis -assembling.
- Hardware troubleshooting of desktop, laptop, server machine.
- Microsoft Windows Servers (2008,2012, 2016 ) operating system installation and troubleshooting
- Microsoft Windows ( XP, 7, 8, 10) operating system installation and troubleshooting.
- Various email client installation and troubleshooting.
- Development software (.Net Framework, MS SQL server / client, Visual studio) installation and troubleshooting.
- Linux ( Ubuntu, CentOS ) installation and troubleshooting. ( Mandatory )
- Various software installations on linux platform.
- Network LAN and WAN troubleshooting.
- VPN management
- Knowledge of Virtualization
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MySQL DBA
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Experience – 8 to 10 years
CTC – 10-12 LPA
Job Description
- 8-10 years of industry experience with an appropriate University technology degree (BE,BTech,MCA)
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- Must be proficient in MS-SQL programming and can handle complex logic.
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We are into digital marketing with our new offering on Neuro Digital Marketing, with big data metrics on social media, so lots of learning and implementation, worked with almost every digital marketing company as a publisher and now we are directly being chased by conglomerates, We own many digital and web/app based products.
Looking for content curator and story teller, who can glue the audience with the help of creative writing, bringing in virality and sentiments attached to it, understands the audience with psychographic segmentation. If it interests you, then join us. Must tell you we are a Startup Full of Zeal and Enthusiasm, and not funded but bootstrapped. But don't worry on about your salary (pun intended).
Kindly don't send resumes due to an heated argument with your boss and you want to switch, but if you think you have spotted your career growth then join us send an email to [email protected], [email protected],
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