Data Scientist

Design, build, and deploy machine learning models to solve complex business problems. These may include predictive analytics, recommendation systems, anomaly detection, classification, and other machine learning tasks. Model Development & Implementation : These tasks include predictive analytics, recommendation systems, anomaly detection, classification, and other machine learning tasks. AI Solutions : Create and optimize AI-driven solutions that can automate processes, improve decision-making, and enhance user experiences across various business functions. Data Analysis & Exploration : Conduct thorough analysis of large datasets to uncover patterns, trends, and insights that inform business strategies and model development. Collaborative Problem Solving : Partner with business stakeholders to understand their goals and challenges, and translate these into data-driven solutions and models that align with the organization’s objectives. Model Optimization : Continuously monitor, fine-tune, and improve the performance of machine learning models through evaluation, experimentation, and iteration. Scalability & Performance : Ensure that AI models and solutions can scale effectively in production environments, handling large volumes of data while maintaining high performance and reliability. Stay Current with AI Trends : Keep up-to-date with the latest advancements in AI, machine learning, and data science to propose innovative techniques and technologies that can drive competitive advantage. Reporting & Communication : Present findings, model results, and actionable insights to both technical and non-technical stakeholders, ensuring clarity and alignment on business impacts. Requirements : Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. Proven experience (5+ years) as a Data Scientist, with a focus on machine learning, AI, and advanced analytics. Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Strong proficiency in programming languages such as Python, R, or similar. Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Keras) and tools for model development, training, and evaluation. Expertise in data manipulation and analysis using tools like Pandas, NumPy, SQL, or similar. Solid understanding of statistical methods, hypothesis testing, and data modeling techniques. Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying models in cloud environments is a plus. Job Details

Seniority level : Associate Employment type : Full-time Job function : Analyst and Research Industries : Broadcast Media Production and Distribution

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