IT – Technology Lead | data science | Machine Learning

POC: Sam ChavezATTENTION ALL SUPPLIERS!!!READ BEFORE SUBMITTING

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MANDATORY: Please include in the resume the candidate’s complete & updated contact information (Phone number, Email address and Skype ID) as well as a set of 5 interview timeslots over a 72-hour period after submitting the profile when the hiring managers could potentially reach to them. PROFILES WITHOUT THE REQUIRED DETAILS and TIME SLOTS will be REJECTED.Job Title: Technology Lead | data science | Machine Learning – Data Scientist
Work Location & Reporting Address: St Louis, MO 63131 (Onsite)
Contract duration: 12
MAX VENDOR RATE: market rate-market rate per hour max
Target Start Date: 13 Mar 2026
Does this position require Visa independent candidates only? YesMust Have Skills:
⦁ Python
⦁ ML Ops
⦁ Generative AI
⦁ LLMs
⦁ Prompt Engineering
⦁ NLPNice to Have Skills:
⦁ AWS
⦁ ETLDetailed Job Description: Minimum Qualifications- Education & Prior Job Experience:
⦁ Lead the full ML development lifecycle: problem framing, hypothesis formulation, feature engineering, model development, validation, deployment, and monitoring.
⦁ Develop, test, and optimize machine learning models including:
o Supervised & unsupervised learning
o Statistical modeling and forecasting
o Natural Language Processing (NLP)
o Generative AI techniques for automation and insight extraction
o Graph/network analytics for analyzing network behaviors and relationships
⦁ Build advanced anomaly detection, predictive maintenance, and risk scoring models for network security and operational efficiency.
⦁ Conduct large-scale exploratory data analysis (EDA) to identify trends, data quality issues, and opportunities for automation.
⦁ Define and implement model evaluation and A/B testing strategies.
⦁ Collaborate with ML engineering teams to operationalize models using MLOps best practices.
⦁ Communicate complex analytical findings through clear narratives, visualizations, and presentations tailored to technical and non-technical audiences.Data Engineering & ETL
⦁ Design, develop, and maintain scalable, fault-tolerant ETL pipelines using Spark to support analytics and machine learning workloads.
⦁ Implement monitoring, alerting, and automated recovery mechanisms to ensure data pipeline reliability.
⦁ Build robust feature pipelines that enable real-time and batch ML processing.
⦁ Integrate data from a wide range of sources:
o APIs
o Flat files
o Relational databases
o Distributed file systems (HDFS/S3)
⦁ Support continuous integration and continuous delivery (CI/CD) workflows for data and ML components.Collaboration & Leadership
⦁ Partner with engineering, operations, security, and business teams to embed machine learning solutions into production systems.
⦁ Provide mentorship to junior data scientists and analysts.
⦁ Evangelize data science best practices across the organization and contribute to the development of internal frameworks, tools, and standards.
⦁ Help educate teams on analytic techniques, statistical reasoning, and responsible AI practices.Required Qualifications
⦁ Strong communication, presentation skills, and ability to translate analytics into business value.
⦁ Expertise in programming languages commonly used in data science:
o Python (primary)
o Scala or Java (preferred for ETL/engineering)
⦁ Proven experience with Spark and large-scale distributed data processing.
⦁ Deep understanding of:
o Statistical modeling
o Hypothesis testing
o Experimental design
o Causality and multicollinearity
⦁ Strong SQL skills and experience with relational and NoSQL databases.
⦁ Expertise across a wide range of ML methodologies:
o Regression, classification, clustering
o Time-series forecasting
o Bayesian methods
o NLP and text analytics
o Graph analytics
⦁ Experience with data preprocessing, feature engineering, and EDA.
⦁ Familiarity with data architectures such as data lakes, warehouses, and marts.
⦁ Demonstrated ability to continuously learn, adapt, and share knowledge.Preferred Qualifications
⦁ Experience with AWS services (S3, EMR, Lambda, Glue, SageMaker).
⦁ Prior exposure to Generative AI, LLMs, prompt engineering, or building AI-driven automation systems.
⦁ Experience with Linux-based systems.
⦁ Background in text mining, document classification, or large-scale unstructured data processing.
⦁ Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering, Operations Research, or a related field.
⦁ Master’s degree with 6 years or Bachelor’s degree with 8 years of relevant work experience.Minimum Years of Experience:
⦁ 8 yearsCertifications Needed:
⦁ NoneTop 3 responsibilities you would expect the Subcon to shoulder and execute:Interview Process (Is face to face required?)
⦁ FACE TO FACE INTERVIEW IS MANDATORYAny additional information you would like to share about the project specs/nature of work:

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