• US Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• W2-Permanent

• W2-Contract

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 17th Nov 2025

• Support ML projects from strategy through implementation and on-going improvements.

• Perform data collection, analysis, validation, cleansing, developing software in support of multiple

machine learning workflows, integrating / deployment of code in a large-scale production

environments and reporting.

• Designs, codes, tests, debugs, and documents ML code - models, ETL processes, SQL queries, and

stored procedures.

• Extracts and analyzes data from various structured and unstructured sources, including databases,

files, data lakes and external APIs/websites.

• Responds to data inquiries from various groups within client’s organization.

• Requires experience with relational databases, document databases (NOSQL) and knowledge of

query tools and/or statistical software.

• Responsible for other duties/projects as assigned by business management / leadership.

Minimum Required

• 12 plus years of experience in statistical modeling, data mining, analytics techniques, machine

learning software development and reporting

• 8 plus years of applied experience in building / deploying Machine Learning solutions using

various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support

Vector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affect

their performance.

• 5 plus years of hands-on experience with Python and/or R programming and statistical

packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.

• 3 plus years of experience in building use cases / solutions especially around AI/

based on Cloud infrastructure and services such as Azure,GCP,AWS cloud platforms and Onpremise

environments

• Expertise with SQL, noSQL, Python, R, Javascript programming languages and big data

environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker,

Kubernetes etc.)

• Experience developing experimental and analytic plans for data modeling processes, using

strong baselines, and determining cause and effect relations.

• Understanding of relevant statistical measures such as confidence intervals, significance of error

measurements, development and evaluation data sets, etc. in data analysis projects.

• Expertise with scaling pilot machine learning solutions to a large scale production environment using databricks

• Expertise with visualization tools such as PowerBI, D3JS etc.

• Excellent written and verbal communication skills.