Data Engineering Analyst

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Data Engineering Analyst

QL2 Software Gurgaon, India

We are looking for a Data Engineering Analyst in Gurgaon, India with a proven track record of leadership, professionalism, partnership, and the ability to get the job done, while holding themselves to the highest degree of honesty and integrity. QL2 is a quickly growing organization and are looking for a Data Engineer who is hungry to be part of the growth and support the organization to help get it to the next level.  The position will be responsible for working with QL2’s data science team to validate and optimize machine learning and deep learning models.  It will support data scientists in the development of new models and moving into production and providing operational support.  The role will provide opportunities to work with true big data and work cross functionally with engineering and analytics teams.


  • Own the optimization and implementation in production of machine learning models
  • Working with Data Science and Engineering teams to test and validate results from models
  • Analyze and interpret model results to lead model enhancement and insights
  • Identify correlations between QL2 Data and external market factors


  • Bachelor’s degree with 2+ years of professional experience.
  • Proficiency in building quantitative models with R or SAS and programming languages (e.g. Python) or similar data tools
  • Proficiency with Linux and cloud providers (AWS preferred)
  • Applied Machine Learning experience (regression analysis, time series, probabilistic models, supervised classification and unsupervised learning).
  • Database knowledge and strong SQL skills.
  • Ability to learn new technologies, perform competitive analysis, and provide recommendations for implementation.
  • Strong understanding of statistics and data analysis
  • Possess excellent communication and inter-personal skills.
  • Proven ability to identify, analyze and solve problems.


  • College diploma or university degree in the field of computer science and at least 2 years equivalent work experience.