Data Scientist, Forge

• Extensive background in data science, statistics, mathematics, or a related field
• 3+ years of building ML pipelines for business application experience
• Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)
• Solid understanding of statistical analysis, data mining techniques, and machine learning algorithms
• Experience in feature engineering, model selection, and hyperparameter optimization
• Proficient in data visualization tools and techniques to effectively communicate complex findings
• Analytical and problem-solving skills with keen attention to detail
• Excellent communication and collaboration skills to work effectively in a multidisciplinary team

Desirable

• We are seeking a highly skilled and innovative Data Scientist to join our scalable machine learning and AI engineering team
• As a Data Scientist, you will play a crucial role in analyzing data, developing models, and implementing cutting-edge algorithms to solve complex problems using machine learning and AI techniques
• Utilize advanced statistical and machine learning techniques to analyze and extract insights from large and complex datasets
• Design and develop predictive models, generative models, classification algorithms, and recommendation systems to address specific business challenges
• Collaborate with cross-functional teams to define outcomes, identify data requirements, and develop strategies for data collection and preprocessing
• Perform exploratory data analysis and feature engineering to extract meaningful features from raw data
• Implement and optimize machine learning algorithms, ensuring scalability and efficiency
• Evaluate and validate models using appropriate evaluation metrics and statistical methods
• Continuously monitor model performance, identify opportunities for improvement, and make recommendations for model enhancements
• Stay updated on the latest advancements in machine learning, AI, and data science, and proactively explore innovative approaches to problem-solving
• Communicate findings and insights to both technical and non-technical stakeholders through visualizations, reports, papers, and presentations