Data Scientist, Sales Operations

What you'll do

• Develop and deploy predictive models using machine learning algorithms for customer segmentation and revenue forecasting.
• Build end-to-end ML pipelines from data ingestion to model deployment to ensure scalability and reliability.
• Create robust time-series forecasting models for revenue, demand, and operational metrics.
• Design and implement generative AI solutions for information retrieval and workflow automation.
• Design and maintain scalable data pipelines using tools like Airflow, KNIME, or shell scripting.
• Perform exploratory data analysis on structured and unstructured data to uncover patterns.
• Develop visualizations using Plotly, Matplotlib, and Seaborn to communicate findings to stakeholders.
• Monitor model performance post-deployment and iterate on models to ensure continued business impact.

What we're looking for

• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.
• Master’s degree in a relevant field (preferred).
• Minimum of 3+ years of experience in data science or related fields.
• Proficiency in Python, SQL, and other programming languages.
• Strong understanding of machine learning algorithms and statistical techniques.
• Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch and generative AI frameworks.
• Experience with big data technologies such as Snowflake, Hadoop, or Spark.
• Experience with version control tools like Git and GitHub.