Career @ Lumiq.ai
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We are a technology company, at a stage where we are moving fast ahead. We have been enabling enterprises to derive the value of Data Science and technology. At Crisp, we are thinking every day about how to use the latest technology and concepts to build products which can help our customers and enterprises in all aspects of their businesses.

Data Engineer

Description

The Data Engineering team is responsible for creating all the Data related products which scale for any amount of data, users and processing. The team also interacts with our customers to work out solutions, create technical architectures and deliver the products and services.

If you are someone who is always pondering how to make things better, how technologies can interact, how a new technology and concept can help the customer or how a customer can use our products, then Crisp is the right place for you.

Day of a Data Engineer here

  • Discusses about the newest innovations in technology with peers and what changes are going to improve the work he is doing
  • Helps in designing the architecture of the project, finds solutions to the existing problems and suggests future improvements to be done
  • Codes the Processing Jobs, Data Pipelines, develops interfaces to interact with the systems
  • Works on Products and Data Platform from end-to-end development
  • Plays around with large clusters on different clouds to tune jobs or to learn
  • Researches about new technologies, proves the concepts and plans how to integrate or update
  • Is the part of discussions of other projects to learn or to help

Who are you?

  • You have 2-5 years of work experience and at least 1 year in Big Data domain.
  • Enthusiast is your middle name. You know what’s new in Big Data technologies and how things are moving
  • Apache is your tool box and you have been a contributor to open source projects or have discussed the problems with the community on several occasions
  • You use cloud for more than just provisioning a Virtual Machine
  • Vim is friendly to you and you know how to exit Nano
  • You check logs before screaming about error
  • You are a solid engineer who writes modular code and commits in GIT
  • You are a doer who don’t say the word impossible
  • You understand the value of documentation of your work
  • You are familiar with Machine Learning Ecosystem and how you can help your fellow Data Scientists to explore data, create training pipelines and serving results
  • You know these buddies - #spark, #hadoop, #nifi, #airflow, #aws, #azure, #gcloud, #emr, #storm, #s3, #cassandra, #dynamodb, #redshift, #kafka, #zookeeper, #docker, #drill, #presto

DevOps Engineer

Description

The DevOps team is a diverse team at Crisp which takes care of automating, integrating the whole development to deployment pipelines of our various line of products and services. It plays a crucial role to make stable and scalable infrastructure of all projects. The team also interacts with our customers and business team to help plan out the infrastructure details.

If you are the one always pondering how to make things better, how technologies can interact, how a new technology and concept would help, then Crisp is the right place for you.

Day of a DevOps Engineer here

  • Discusses about the newest innovations in scalable and distributed systems
  • Helps in designing the architecture of the project, solutions to the existing problems and future improvements to be done
  • Makes the cloud infrastructure and services smart by implementing automation and trigger based solutions
  • Interacts with Data Engineers and Application Engineers to create continuous integration and deployment frameworks and pipelines
  • Plays around with large clusters on different clouds to tune your jobs or to learn
  • Researches about new technologies, proves the concepts and plans how to integrate or update
  • Is the part of discussions of other projects to learn or to help

Who are you?

  • You have 2-5 years of work experience and at least 1 year in DevOps domain.
  • You have worked on containers (Docker) and their orchestration systems (Kubernetes, Mesos)
  • You can secure systems by creating robust access policies and network restrictions enforcement
  • You understand that knowledge about how applications work is very important to design distributed systems
  • You have contributed to open source projects and have discussed the shortcomings or problems with the community on several occasions
  • You know Provisioning a Virtual Machine is not DevOps
  • You know you are not a SysAdmin but a DevOps Engineer who is the person behind developing operations for the system to run efficiently on scale
  • You understand Private Cloud, subnets, vpns, peering, load balancers and have worked with them
  • ssh is your way to enter a room
  • Vim is friendly to you and you know how to exit Nano
  • You check logs before screaming about error
  • Multiple Screens make you more efficient
  • You are a doer who doesn’t say the word impossible
  • You understand the value of documenting your work
  • You understand the Big Data ecosystem and how you can leverage cloud for it
  • You know these buddies - #airflow, #aws, #azure, #gcloud, #s3, #docker, #kubernetes, #mesos, #acs, #jenkins

Data Scientist

Description

The Data Science team is the brain behind all the intelligence our products deliver. The team is responsible to map business understanding to technical understanding and implementation. From Exploration to Model Deployment, this team enables the industrialization of the Machine Learning in true sense.

If you are the one always pondering how to make things better, how technologies can interact, how a new technology and concept would help, then Crisp is the right place for you.

Day of a Data Scientist here

  • Discusses about the new research paper released in his/her area of work
  • Interacts with Data Engineering team for data requirements
  • Excel, Jupyter Notebook, Visualization tools are always open with some data for exploration there
  • Discusses with engineering team to create the machine learning pipeline and how it can be made more efficient
  • A lot of wall and board scribbling with Maths and numbers which scares others

Who are you?

  • You have at least 2 years of work experience in Data Science.
  • You have a strong primary expertise as data scientist, with the ability to stretch beyond one’s core field of expertise.
  • You have PhD or Master at least 2+ years of *relevant experience* as a strong contributor on a data science team
  • You have a relevant degree in Statistics, Math/Applied Math, Operations Research, Computer Science, Economics or Quantitative Finance
  • You have expertise in at least one analytics function: attribution, segmentation, response modeling, churn, propensity, customer LTV, supply chain / logistics, geospatial inference, recommender systems, causal inference, forecasting, pricing, NLP or image processing
  • You are proficient in R/Python, particularly to prototype mathematical models
  • You know SQL and are familiar working with at least one of the tools - Tableau, R-Shiny/or other data visualization tools
  • You are able to scope and define data sets needed for specific use cases and identifying data gaps
  • You are able to translate scientific insights into product decisions and work streams
  • You have good communication skills
  • You can manage customers – ability to lead and persuade, positive energy, relentless focus on business impact