Compunnel Inc.
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a contract length of "unknown," offering a pay rate of "unknown." Key skills include SQL, PySpark, Python, and experience with AWS/Azure. Requires 2+ years in statistical techniques and customer segmentation.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 17, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Irving, TX
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🧠 - Skills detailed
#Spark (Apache Spark) #AI (Artificial Intelligence) #Deployment #Customer Segmentation #Data Science #Docker #Kubernetes #Databricks #A/B Testing #Azure #ML (Machine Learning) #Python #SQL (Structured Query Language) #Libraries #PySpark #AWS (Amazon Web Services) #Computer Science
Role description
· Customer segmentation: Building, evaluating, and deploying models to identify and target customer segments for personalized experiences and marketing.
· Online controlled experiments: Designing, running, and analyzing A/B tests and other online experiments to measure the impact of new features, campaigns, and product changes.
Key Responsibilities
· Research, prototype, and develop AI solutions for personalized systems and customer segmentation.
· Design and analyze online controlled experiments (A/B tests) to validate hypotheses and measure business impact.
· Build, deploy, and analyze AI solutions; perform statistical experiments when deploying new AI products.
· Stay up to date with emerging technology and learn new technologies/libraries/frameworks.
· Collaborate with peers across data, product, and systems design disciplines.
· Deliver on time with a high bar for research, innovation, and engineering quality.
· Translate business goals into data science problems and communicate results to non-technical audiences. Proven track record of driving measurable impact through data science in marketing contexts.
Basic Qualifications
· 2+ years of experience with statistical data science techniques, feature engineering, and customer segmentation.
· 2+ years of experience with SQL, PySpark, and Python.
· 2+ years of experience training, evaluating, and deploying machine learning models.
· 2+ years of experience productionizing and deploying ML workloads in AWS/Azure.
· Familiarity with containerized application tooling and deployments (Docker/Kubernetes).
· Bachelor’s Degree or higher in Computer Science/Engineering/Math, or relevant experience.
Extra Credit
· Experience with Databricks platform.
· Experience building ML models with large amounts of structured and unstructured data.
· Experience working with MarTech platforms (e.g., CDPs, DMPs, ESPs) and integrating data science into marketing workflows.
· Customer segmentation: Building, evaluating, and deploying models to identify and target customer segments for personalized experiences and marketing.
· Online controlled experiments: Designing, running, and analyzing A/B tests and other online experiments to measure the impact of new features, campaigns, and product changes.
Key Responsibilities
· Research, prototype, and develop AI solutions for personalized systems and customer segmentation.
· Design and analyze online controlled experiments (A/B tests) to validate hypotheses and measure business impact.
· Build, deploy, and analyze AI solutions; perform statistical experiments when deploying new AI products.
· Stay up to date with emerging technology and learn new technologies/libraries/frameworks.
· Collaborate with peers across data, product, and systems design disciplines.
· Deliver on time with a high bar for research, innovation, and engineering quality.
· Translate business goals into data science problems and communicate results to non-technical audiences. Proven track record of driving measurable impact through data science in marketing contexts.
Basic Qualifications
· 2+ years of experience with statistical data science techniques, feature engineering, and customer segmentation.
· 2+ years of experience with SQL, PySpark, and Python.
· 2+ years of experience training, evaluating, and deploying machine learning models.
· 2+ years of experience productionizing and deploying ML workloads in AWS/Azure.
· Familiarity with containerized application tooling and deployments (Docker/Kubernetes).
· Bachelor’s Degree or higher in Computer Science/Engineering/Math, or relevant experience.
Extra Credit
· Experience with Databricks platform.
· Experience building ML models with large amounts of structured and unstructured data.
· Experience working with MarTech platforms (e.g., CDPs, DMPs, ESPs) and integrating data science into marketing workflows.
