Exl Service

Sr. Data Scientist

Job Location US-NJ-Jersey City
Temporary Full-Time
Job Code


Data Scientist / Sr. Data Scientist


EXL (NASDAQ:EXLS) is a leading operations management and analytics company that helps businesses enhance growth and profitability in the face of relentless competition and continuous disruption. Headquartered in New York, New York, EXL has offices in United States, Europe, Asia, Latin America, Australia and South Africa.


EXL Analytics provides data-driven, action-oriented solutions to business problems through statistical data mining and cutting edge analytics techniques. Leveraging proprietary methodology and best-of-breed technology, EXL Analytics takes an industry-specific approach to transform our clients’ decision making and embed analytics more deeply into their business processes. EXL Analytics serves clients across industries including healthcare, banking, insurance, retail and logistics.


Please visit www.exlservice.com for more information about EXL Analytics.


Job Summary:

EXL Analytics is developing advanced analytics solutions for some of the most exciting business problems leveraging AI, NLP, Computer Vision and Speech. If you want to push the existing AI knowledge boundaries then we have an excellent opportunity for you. We are looking for Data Scientists who can develop state of the art, scalable, and self-learning systems for enterprises.  Major responsibility will be to develop advanced analytics solutions focusing on machine learning and deep learning capabilities.


  • Work with large, complex data sets. Solve difficult, non-routine problems, applying advanced analytical methods
  • Focus on creating state of the art, scalable, and self-learning systems for enterprises. This includes training and tuning a variety of machine learning / deep learning models
  • Rapidly prototype products based on the latest technologies in the related fields
  • Experiment and develop machine learning algorithms for tasks including document processing, image processing and speech analytics
  • Deploy and productionize machine learning / deep learning models used in large scale systems
  • Take ownership of whole end-to-end machine learning systems - from data processing, training, optimization to real-time monitoring and maintenance


  • Minimum 5 years of experience (including graduate school) developing machine learning models, applying and developing advanced analytics solutions
  • Education:  MS or PhD S degree in a quantitative discipline e.g., computer science, mathematics, physics, electrical engineering, statistics, operations research, bioinformatics, econometrics, artificial intelligence, computer linguistics, etc.
  • Experience with Computer Vision / Natural Language Processing methods is preferred
  • Applied experience of machine learning algorithms using Python/Java. Production level coding experience in Python/Java is required
  • Organized, self-motivated, disciplined and detail oriented
  • Ability to read recent Machine Learning and Deep Learning research papers and adapt those models to solve real-world problems
  • Experience with any deep learning framework, including Tensorflow, Caffe, MXNet, Torch, Theano is a plus
  • Experience with optimization on GPUs (a plus)

What we offer:

  • EXL Analytics offers highly competitive compensation in the field of data science
  • We offer an exciting, fast paced and innovative environment, which brings together a group of sharp and entrepreneurial professionals who are eager to influence business decisions. From your very first day, you get an opportunity to work closely with highly experienced, world class analytics consultants.
  • You can expect to learn many aspects of businesses that our clients engage in. You will also learn effective teamwork and time-management skills - key aspects for personal and professional growth
  • Sky is the limit for our team members. The unique experiences gathered at EXL Analytics sets the stage for further growth and development in our company and beyond.


EEO Statement



Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
Share on your newsfeed