Data Scientist

At 8fig we're not just a growth platform we're a catalyst for eCommerce brands, leveraging AI planning and funding to propel them to unprecedented success. Our mission is to empower sellers with cutting-edge AI technology and essential financial tools, enabling them to achieve 8-figure revenues and beyond.

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 from scratch predictive models, generating actionable insights, and driving strategic initiatives to optimize our product offerings.

Responsibilities:

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 in a clear and concise manner.

Requirements:

Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
3+ 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 process, stochastic process, 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 PySpark, airflow, dbt.