Account Manager - Data Science

Job Description:

Key Responsibilities:

Data Modeling & Analysis:

• Design, implement, and optimize data models to support various business operations and decision-making processes.
• Develop scalable, high-performance data architectures to manage and analyze large datasets.
• Ensure the accuracy, consistency, and reliability of data across platforms.

Generative AI & AI Agents:

• Develop and deploy Generative AI models and AI agents to automate tasks and generate insights, improving business processes.
• Work on integrating AI-driven solutions that enhance productivity, customer engagement, and decision-making.
• Apply machine learning techniques to build intelligent systems that improve over time through interaction.

Machine Learning & Predictive Analytics:

• Build and tune machine learning models (supervised and unsupervised) to predict trends, identify patterns, and optimize business operations.
• Collaborate with data engineers to ensure seamless deployment of models into production environments.

SQL & Python Development:

• Write complex SQL queries to extract, clean, and manipulate data from various sources.
• Use Python for advanced data analysis, machine learning, and AI model development, ensuring models are scalable and maintainable.

Collaboration & Communication:

• Partner with business teams, product managers, and engineers to ensure data models and AI solutions align with organizational goals.
• Provide clear and concise explanations of data findings, model outputs, and actionable insights to both technical and non-technical stakeholders.

Required Skills and Qualifications:

• Experience: 5+ years of experience in data science, data modeling, and AI technologies.
• SQL & Python: Strong hands-on experience in SQL for querying databases and Python for data manipulation, machine learning, and AI.
• Generative AI & AI Agents: Practical experience working with Generative AI, including creating and deploying AI agents for real-world applications.
• Machine Learning & Analytics: Knowledge of supervised/unsupervised learning, predictive modeling, and data analysis techniques.
• Problem-Solving: Strong analytical skills and the ability to handle complex datasets to derive actionable insights.
• Communication: Excellent communication skills to present complex data concepts and findings to business leaders in a clear, understandable way.

Preferred Qualifications:

• Experience with deep learning libraries such as TensorFlow or PyTorch.
• Familiarity with cloud-based platforms (e.g., AWS, Azure, Google Cloud) for AI and data processing.
• Experience with natural language processing (NLP) or computer vision technologies.
• Understanding of DevOps and model deployment practices for AI models in production

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