Data Science Senior Analyst

Key Skills

AWS, Azure, Data Analytics, Data science techniques, DevOps, Machine learning techniques, MLOps tools

Job Description

Data Science Senior Analyst:

Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Machine Learning Services and Pipelines.

You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments.

Responsibilities

• Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
• Active contributor to code & development in projects and services
• Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.
• Partner with ML engineers working on industrialization.
• Communicate with business stakeholders in the process of service design, training and knowledge transfer.
• Support large-scale experimentation and build data-driven models.
• Leverage big data technologies to help process data and build scaled data pipelines (batch to real time)
• Implement end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines

Qualifications

• and contributing to ML OPS automation infrastructure is good to have
• BE/B.Tech in Computer Science, Maths, technical fields.
• Overall 9+ years of experience working as a Data Scientist.
• 6+ years’ experience building solutions in the commercial or in the supply chain space.
• 6+ years working in a team to deliver production level analytic solutions. Fluent in git (version control). Understanding of Jenkins, Docker are a plus.
• Fluent in SQL syntaxis.
• 6+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.
• 6+ years’ experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python and Pyspark development.
• Experience executing Exceptional analytical and problem-solving skills
• Experience in DevOps, hands-on experience with one or more cloud service providers AWS, GCP, Azure(preferred)