Akkodis

Senior Data Scientist-Insurance

โญ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist in the insurance sector, offering a 4-month contract at $90-$95/hr, remote from Chicago, IL. Key skills include machine learning, NLP, Python, SQL, and experience with insurance claims analytics. A Master's degree is preferred.
๐ŸŒŽ - Country
United States
๐Ÿ’ฑ - Currency
$ USD
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๐Ÿ’ฐ - Day rate
760
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๐Ÿ—“๏ธ - Date
June 30, 2026
๐Ÿ•’ - Duration
Unknown
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๐Ÿ๏ธ - Location
Remote
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๐Ÿ“„ - Contract
Unknown
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๐Ÿ”’ - Security
Yes
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๐Ÿ“ - Location detailed
United States
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๐Ÿง  - Skills detailed
#Snowflake #Looker #Computer Science #Classification #Monitoring #Datasets #ML (Machine Learning) #Data Profiling #Data Engineering #EDW (Enterprise Data Warehouse) #Mathematics #AWS (Amazon Web Services) #Model Evaluation #Security #Data Science #NLP (Natural Language Processing) #Microsoft Power BI #AWS SageMaker #BI (Business Intelligence) #Tableau #Statistics #Data Cleaning #Python #Cloud #Model Validation #SageMaker #SQL (Structured Query Language) #Batch #Data Warehouse #Data Governance #"ETL (Extract #Transform #Load)"
Role description
Akkodis is seeking a Senior Data Scientist for a 4-month contract role with a client in Chicago, IL-Remote. Title: Senior Data Scientist Location: Chicago, IL-Remote Duration: 4-month Contract Pay Rate: $90/hr - $95/hr (The rate may be negotiable based on experience, education, geographic location, and other factors) Purpose: The Sr Data Scientist will design and implement machine learning and NLP solutions for a claims and incident mitigation analytics project. This role will help risk management teams identify high-risk incidents earlier, classify claims by likely severity and financial impact, and provide explainable insights that support faster intervention. The position responsibilities outlined below are not all-encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary. Position Responsibilities: โ€ข Translate risk management business requirements into well-defined data science solutions, including incident prioritization and claim severity classification. โ€ข Profile, clean, and prepare claims and incident data for analytics, modeling, and scoring. โ€ข Develop feature engineering logic using structured and unstructured claims and incident data. โ€ข Apply NLP and text-processing techniques to claim and incident narratives to extract useful risk signals. โ€ข Develop record-linkage approaches to connect incidents and claims when a clean unique identifier is not available. โ€ข Build and validate models that rank incidents by likelihood of becoming claims or requiring Risk Management intervention. โ€ข Build and validate claim severity models that classify claims by likely financial impact and high-dollar claim risk. โ€ข Generate explainability outputs, including key risk drivers and business-readable reasons for flagged incidents or claims. โ€ข Collaborate with Risk Management, Legal, Data Engineering, BI, Data Governance, and MLOps partners to deliver usable business outputs. โ€ข Monitor model performance, drift, scoring quality, and retraining needs. โ€ข Document modeling assumptions, feature logic, validation results, limitations, and handoff requirements. โ€ข Ensure data science work follows data governance expectations, including appropriate handling of PII and sensitive fields. โ€ข Present findings, model results, and recommendations to business and technical stakeholders in a clear, actionable manner. Experience and qualifications: Required Skills - โ€ข Strong experience building supervised machine learning models, especially classification, ranking, and severity/risk scoring models. โ€ข Strong experience with data profiling, data cleaning, feature engineering, model validation, and model evaluation. โ€ข Experience working with messy, sparse, real-world enterprise datasets. โ€ข Strong Python and SQL skills. โ€ข Experience with NLP or text analytics, including narrative cleaning, text classification, embeddings, keyword extraction, or summarization. โ€ข Experience with probabilistic record linkage, entity resolution, fuzzy matching, or deduplication. โ€ข Experience explaining model outputs using feature importance, SHAP, reason codes, or other explainability methods. โ€ข Experience working with Snowflake or similar enterprise data warehouse platforms. โ€ข Experience supporting batch scoring, model monitoring, and production handoff. โ€ข Strong understanding of data governance, sensitive data handling, and PII masking or exclusion. โ€ข Excellent communication and teamwork skills. Preferred Skills: โ€ข Experience with insurance claims, risk management analytics, litigation analytics, fraud detection, or safety analytics. โ€ข Experience with claim severity modeling or high-dollar claim prediction. โ€ข Experience with AWS, SageMaker, or similar cloud-based data science environments. โ€ข Experience supporting BI outputs in Tableau, Power BI, Looker, or similar tools. โ€ข Familiarity with MLOps best practices, model versioning, monitoring, and retraining workflows. โ€ข Exposure to hospitality, property operations, guest experience, or enterprise safety data. โ€ข Proven ability to translate complex analytics into practical business workflows and measurable impact. Education: Master's degree in computer science, statistics, data science, industrial engineering, operations research, mathematics, or related field preferred. Bachelor's degree with strong relevant experience acceptable. Equal Opportunity Employer/Veterans/Disabled Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, an EAP program, commuter benefits, and a 401K plan. Our benefit offerings provide employees the flexibility to choose the type of coverage that meets their individual needs. In addition, our associates may be eligible for paid leave including Paid Sick Leave or any other paid leave required by Federal, State, or local law, as well as Holiday pay where applicable. Disclaimer: These benefit offerings do not apply to client-recruited jobs and jobs that are direct hires to a client. To read our Candidate Privacy Information Statement, which explains how we will use your information, please visit https://www.akkodis.com/en/privacy-policy. The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable: ยท The California Fair Chance Act ยท Los Angeles City Fair Chance Ordinance ยท Los Angeles County Fair Chance Ordinance for Employers ยท San Francisco Fair Chance Ordinance