• 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.

• 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.

• Experience with large-scale data processing frameworks and distributed systems (e.g., Spark, Hadoop) is a plus.
• Familiarity with cloud platforms and their machine learning services (e.g., AWS, Google Cloud) is desirable.
• Previous experience in a similar role or projects demonstrating practical application of machine learning and AI techniques is preferred.
• Financial Services Background
• Experience with modeling tools such as scikit-learn, Tensorflow, numpy, pandas, scipy etc.
• Experience with cloud technologies such as AWS Step Functions, Sagemaker, Lambda, Glue or similar.
• Experience building web APIs

For residents of San Francisco/Bay Area, CA or New York, NY the annual salary range for this role is $160,000 - $170,000 + bonus & equity. Final offers may vary from the amount listed based on geography, candidate experience and expertise, bonus, and other factors

Forge implements a mandatory COVID-19 Vaccination Policy, which applies to all employees. All employees covered by this policy are required to be fully vaccinated as a term and condition of employment at Forge. Employees are considered fully vaccinated two weeks after completing primary vaccination with a COVID-19 vaccine, with, if applicable, at least the minimum recommended interval between doses. Employees must provide truthful and accurate information about their COVID-19 vaccination status, and, if applicable, their testing results as of the first date of their employment.

Employees may request an exception from this mandatory vaccination policy if the vaccine is medically contraindicated for them or medical necessity requires a delay in vaccination. Employees also may be legally entitled to a reasonable accommodation if they cannot be vaccinated because of a disability, or if the provisions in this policy for vaccination conflict with a sincerely held religious belief, practice, or observance. All such requests will be handled in accordance with applicable laws and regulations.