Data Scientist

We are looking for a highly skilled and innovative Data Scientist to join our team at Forge. As a Data Scientist, you will be responsible for analyzing data, developing models, and implementing cutting-edge algorithms using machine learning and AI techniques. Your role will involve utilizing advanced statistical and machine learning techniques to extract insights from complex datasets, designing and developing predictive models and recommendation systems, and collaborating with cross-functional teams to define outcomes and data requirements. Additionally, you will be responsible for performing exploratory data analysis, implementing and optimizing machine learning algorithms, and continuously monitoring and improving model performance.

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.

• 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.

• Competitive annual salary range of $160,000 - $170,000 + bonus & equity (may vary based on factors such as geography, candidate experience, and expertise)
• Mandatory COVID-19 Vaccination Policy for all employees
• Opportunity to work in a diverse and inclusive environment
• Extensive background in data science, statistics, mathematics, or a related field
• 3+ years of experience in building ML pipelines for business applications
• Proficiency in programming languages such as Python or R
• Experience with machine learning libraries such as 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
• Analytical and problem-solving skills with keen attention to detail
• Excellent communication and collaboration skills
• 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