Data Science / ML Data Engineer

Exusia-posted 4 months ago

Full-time • Mid Level

251-500 employees

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Exusia, a cutting-edge digital transformation company, seeks a Data Scientist to join our global delivery team's Data Engineering & Analytics practice in the United States. The Data Scientist role will be part of our Data Engineering & Analytics practice and will be focused on delivering best of breed solutions to our clients leveraging Advanced Analytics & Machine Learning tools and techniques. The candidate will also be part of the practice team and contribute to Competency development, driving innovation through various internal initiatives within the company.

Work on client projects to deliver Data insights using AI, ML and Advanced analytics techniques
Architect, Build & Deploy scalable Machine Learning models both on premise & on cloud platforms
Work with the business stakeholders to Identify problem statement, check availability of data and identify appropriate solutions to provide insights to address the problems and deliver better outcomes
Work closely with the data engineering teams to source and ingest data into data lakes
Look at semi structured and unstructured data and propose solutions to translate them into structured data format to provide better insights
Collaborate with S & D leadership to propose and execute ML POCs to deliver quick wins for the clients
Providing mentorship to junior resources within the data scientist community

Should have 6+ years of experience working in Business Intelligence, Analytics and Machine Learning
Extensive hands-on experience analyzing data with SQL
Experience in data mining of large data sets using tools like SAS / R / Python to identify patterns
Experience in using tools like Alteryx or Python libraries like Pandas for preprocessing & cleaning data
Experience using BI tools like Tableau or PowerBI for self-service analysis and Visualization of data
Document processing using OCR conversion techniques
Collaborate with data engineering teams to ingest unstructured & semi structured data into data lakes
Identify data sets, attributes and patterns to propose appropriate ML approach for a given problem
Strong fundamentals in statistics and its application for building and validating ML models
Understanding of Supervised, Unsupervised and Reinforcement learning approaches
Strong experience in using Regression / Classification / Clustering algorithms and their application for appropriate use cases
Build models using R, Python or Cloud native ML offerings from AWS, AZURE and GCP platforms
Deploy ML models at scale using tools like TensorFlow Serving, Sagemaker, Torchserve
Problem-solving skills along with good interpersonal & communication skills

Exposure to Azure, AWS and Google Cloud Platforms with hands on exposure to ML service offerings
Experience working with teams located in multiple locations across the globe
Knowledge and understanding of various Data repositories, Databases, ETL and BI tools and data assets hosted on Hadoop or cloud platforms
Agile development experience & collaborating with data engineering teams
Familiarity with Spark, Scala and distributed data processing platforms will be a big advantage
Ability to work with tools like Jupyter / Databricks notebooks to interactively work with data sets

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