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Data Scientist
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Jobs via Dice . Dice is the leading career destination for tech experts at every stage of their careers. Our client, Kforce Technology Staffing, is seeking a Data Scientist. Apply via Dice today! Responsibilities:
Research, prototype, and develop AI solutions to build personalized systems. Build, deploy, and analyze AI solutions; perform statistical experiments when deploying new AI products. Stay updated with emerging technologies and learn new frameworks and libraries. Collaborate with peers across data, product, and systems design disciplines. Deliver high-quality research, innovation, and engineering on time. Requirements:
Bachelor's degree or higher in Computer Science, Engineering, Math, or related field. 2+ years of experience with statistical data science techniques, feature engineering, customer segmentation, etc. 2+ years of experience with SQL, PySpark, and Python. 2+ years of experience training, evaluating, and deploying Machine Learning models. Experience with productionizing ML workloads in AWS/Azure. Familiarity with containerized applications (Docker/Kubernetes). Nice to Have:
Experience with Databricks platform. Experience building ML models with large structured and unstructured data. Additional Skills:
Statistical Data Science SQL PySpark Databricks (plus) Customer Data & Recommendations Systems (plus) Customer Segmentation (plus) This job is active and accepting applications. #J-18808-Ljbffr
Data Scientist
role at
Jobs via Dice . Dice is the leading career destination for tech experts at every stage of their careers. Our client, Kforce Technology Staffing, is seeking a Data Scientist. Apply via Dice today! Responsibilities:
Research, prototype, and develop AI solutions to build personalized systems. Build, deploy, and analyze AI solutions; perform statistical experiments when deploying new AI products. Stay updated with emerging technologies and learn new frameworks and libraries. Collaborate with peers across data, product, and systems design disciplines. Deliver high-quality research, innovation, and engineering on time. Requirements:
Bachelor's degree or higher in Computer Science, Engineering, Math, or related field. 2+ years of experience with statistical data science techniques, feature engineering, customer segmentation, etc. 2+ years of experience with SQL, PySpark, and Python. 2+ years of experience training, evaluating, and deploying Machine Learning models. Experience with productionizing ML workloads in AWS/Azure. Familiarity with containerized applications (Docker/Kubernetes). Nice to Have:
Experience with Databricks platform. Experience building ML models with large structured and unstructured data. Additional Skills:
Statistical Data Science SQL PySpark Databricks (plus) Customer Data & Recommendations Systems (plus) Customer Segmentation (plus) This job is active and accepting applications. #J-18808-Ljbffr