Dieses Stellenangebot ist nicht mehr verfügbar
Über
ATTENTION ALL SUPPLIERS!!!
READ BEFORE SUBMITTING • UPDATED CONTACT NUMBER and EMAIL ID is a MANDATORY REQUEST from our client for all the submissions • Limited to 1 submission per supplier. Please submit your best. • We prioritize endorsing those with complete and accurate information • Avoid submitting duplicate profiles. We will Reject/Disqualify immediately. • Make sure that candidate's interview schedules are updated. Please inform the candidate to keep their lines open. • Please submit profiles within the max proposed rate. • Please make sure to TAG the profiles correctly if the candidate has WORKED FOR INFOSYS as a SUBCON or FTE. 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: per hour max Target Start Date: 13 Mar 2026 Does this position require . independent candidates only? Yes
Must Have Skills: ? Python ? ML Ops ? Generative AI ? LLMs ? Prompt Engineering ? NLP
Nice to Have Skills: ? WS ? ETL
Detailed 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 years
Certifications Needed: ? None
Top 3 responsibilities you would expect the Subcon to shoulder and execute:
Interview Process (Is face to face required?) ? FACE TO FACE INTERVIEW IS MANDATORY
Any additional information you would like to share about the project specs/nature of work:
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot wurde von einem unserer Partner veröffentlicht. Sie können das Originalangebot einsehen hier.