Data scientist

Description About 8fig: At 8fig, we’re building the future of eCommerce funding. Our AI-powered platform analyzes real-time sales and banking data to offer personalized, flexible growth plans tailored to each business. By combining smart capital with powerful planning tools, we empower eCommerce businesses to scale sustainably and strategically - on their terms. About the Role As a Data Scientist at our company, you will play a pivotal role in advancing our data-driven initiatives, focusing on Time-Series modeling and NLP modeling. Leveraging your expertise in statistical modeling, machine learning, and financial knowledge, you will be instrumental in developing predictive models from scratch, generating actionable insights, and driving strategic initiatives to optimize our product offerings. What You’ll Do Conduct in-depth analysis of Time-Series data to identify trends, patterns, and anomalies. Develop and implement End-to-End advanced Time-Series forecasting and NLP models to predict future trends and outcomes. Develop End-to-End models based on multiple data sources. Collaborate with cross-functional teams to integrate data science solutions into our product offerings. Collaborate with cross-functional teams, including product managers and engineers, to translate business requirements into data science solutions that drive data-driven decision-making and automate processes. Utilize statistical techniques and machine learning algorithms to extract valuable insights from complex data sets. Apply domain-specific knowledge in the financial sector to optimize predictive models and enhance data-driven decision-making. Communicate findings and recommendations to stakeholders clearly and concisely. What you bring: Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. 4+ years of proven experience working as a Data Scientist in a product-focused company. Strong expertise in Time-Series data analysis, modeling, and forecasting techniques (e.g., non-stationary processes, stochastic processes, survival analysis, ARIMA, LSTM, Prophet, etc.) Proficiency in Python and data manipulation tools like pandas, NumPy, and scikit-learn. Familiarity with financial concepts and metrics, with the ability to apply them to data science projects. Excellent analytical skills, problem-solving abilities, and a passion for leveraging data to drive business outcomes. Strong communication skills to effectively collaborate with team and cross-team members and present findings to stakeholders. Advantages: NLP modeling Familiarity with financial concepts and Financial Engineering techniques Familiarity with PySpark, Airflow, and dbt.