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Associate- MLOps

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Job Description - Associate- MLOps


Job Description: Associate (Analytics)


Zenon Analytics is a global boutique consulting firm and the leading AI partner for Fortune 500 firms. We partner with clients across the globe to identify their highest-value opportunities, address their most critical challenges, and transform their enterprises using advanced analytics.


In a nutshell:


An Associate (Analytics) at Zenon Analytics is responsible for analysing data and deriving actionable insights for timely decision making by our clients. A person in this role will be responsible for client engagements, understanding client requirements, problem structuring, extracting requisite data, performing extensive data analyses and building statistical & predictive models.

The ideal candidate should have exceptional coding skills (Python/R), strong analytical skills including theoretical and practical knowledge of putting ML models into production. The ideal candidate should also possess excellent soft skills to support client engagements.

They will work closely with highly experienced leaders in designing, developing and implementing cutting-edge analytics solutions for a variety of business problems.


What will you do?


  • Engage with clients to understand their business needs from an analytical standpoint and accordingly define the problem statement(s) to focus on.
  • Understand the data requirements to solve the problem and perform exhaustive exploratory analyses.
  • Build statistical and/or predictive models on the data to assist in better business decision making. Test the performance of the models and deploy them into production by closely working with the client teams
  • Prepare client deliverables, followed by engaging with the clients to discuss results and recommendations.
  • Be passionate about applying analytics to real-world business situations and producing measurable improvements for clients.
  • Be comfortable with ambiguity and truly enjoy the challenge of creating new solutions for difficult Big Data problems.
  • Bring in analytical expertise to assist with Business Development proposals.


What are we looking for?


  • Strong academic background, preferably from Tier I institutes with a major in Engineering/Mathematics/Statistics
  • Self-driven, with the ability to work in a fast paced, dynamic environment
  • 3-6 years of experience in putting ML models into production
  • Analytical thinker with strong problem structuring and solving abilities
  • Ability to work in a systematic manner with focus on quality of work and efficiency
  • Strong communication skills


MLops and Data Science expertise -


  • Hands-on experience in Python , R, SQL
  • Knowledge of building traditional and advanced ML models for structured and unstructured data and putting models into production
  • Expertise in one of API frameworks like FastAPI, Flask etc.
  • Engineering Deep hands-on experience with one or more of the following Cloud and AI technologies: Cloud-native architectures (Containers, Kubernetes, Serverless) DataOps, MLOps (Kubeflow, Ray) Tightly-coupled and Loosely-coupled HPC frameworks Deep Learning, ML Frameworks (PyTorch, TensorFlow)
  • Knowledge of infrastructure stacks at-least one. (AWS, Azure, GCP, Docker, Kubernetes, Kafka, Spark, etc.)
  • Experience in agile development, utilizing Git, MLFlow CI/CD, and MLOps frameworks.
  • Architecture - the ability to create and explain 3-tier architecture diagrams, system context diagrams, system interaction diagrams, etc.
  • Model Management, MLOps, Model Deployment approaches, Model monitoring and tuning with respect to at-least one of the major cloud providers
  • Hands on working experience on at least one of the MLOps Platform like AWS Sagemaker, Dataiku, Data Robot etc.
  • Knowledge to design a solution approach, leading a team to deploy and maintain it in production.


Good to have experience


  • Financial services or Healthcare industry experience will be a plus
  • Experience in UiPath AI Fabric
  • Worked on Cloud AWS
  • Experience in bigdata Hadoop, Teradata
  • PySpark exposure



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