Data Scientist

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November 9

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AGENTIC

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Artificial Intelligence • B2B • Enterprise

AGENTIC is a B2B conference and event series focused on the autonomous AI era, convening enterprise leaders, builders, policymakers, and vendors to explore and operationalize AI agents, generative AI, and automation. The event offers keynotes, workshops, executive roundtables, and an interactive "Vibe Lounge" to showcase tools, enable hands-on demos, and drive measurable, outcomes-focused connections between buyers and solution providers across industries like healthcare, finance, retail, manufacturing, media, and government. AGENTIC emphasizes trust-driven growth, responsible AI governance, and practical deployment strategies to help organizations adopt AI at scale.

11 - 50 employees

Founded 2017

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

📋 Description

• Develop and deploy machine learning models for predictive analytics, recommendation systems, NLP, and computer vision • Perform statistical analysis and data exploration to extract actionable insights • Design and implement AI/ML algorithms, including supervised and unsupervised learning techniques • Utilize Deep Learning frameworks (TensorFlow, PyTorch) for complex AI tasks • Work with big data processing frameworks such as Apache Spark and Dask • Collaborate with Data Engineers to optimize data pipelines and feature engineering • Implement model monitoring, validation, and optimization techniques • Use A/B testing and experimentation to refine models and improve decision-making • Deploy AI solutions in cloud environments (AWS, Azure, GCP) • Stay updated with AI/ML research trends and integrate state-of-the-art techniques into business applications

🎯 Requirements

• Proficiency in AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn • Strong understanding of supervised, unsupervised, and deep learning models • Experience in data analysis and visualization (Pandas, NumPy, Matplotlib, Seaborn) • Hands-on experience with SQL and NoSQL databases for data retrieval and processing • Proficiency in Python, R, or Julia for machine learning and data analysis • Experience with cloud AI services (AWS SageMaker, Google Vertex AI, Azure ML) • Strong knowledge of time-series forecasting, NLP, and recommendation systems • Experience in A/B testing, experimentation, and model performance evaluation • Familiarity with MLOps tools (MLflow, Kubeflow) for model deployment and tracking

🏖️ Benefits

• 100% remote role with a flexible schedule • Opportunities for growth and continuous learning in Data Science and AI • Engage in innovative projects that create real-world impact