Data Scientist, Sales Operations

What you'll do

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

What we're looking for

• Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field (Master's preferred).
• Minimum of 3+ years of experience in data science or related fields.
• Proficiency in Python and SQL for data analysis and programming.
• Strong understanding of machine learning algorithms, statistical techniques, and time-series forecasting methods.
• Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch and frameworks for generative AI.
• Experience working with big data technologies such as Snowflake, Hadoop, or Spark.
• Basic knowledge of UNIX shell scripting (Bash, Zsh) and version control tools like Git and GitHub.
• Ability to translate technical insights into actionable business strategies and communicate effectively with cross-functional teams.