Sr. Data Scientist

About the role

6sense is seeking a Senior Data Scientist to join their team in San Francisco. In this role, you will apply advanced statistical methods and machine learning techniques to solve complex business problems. The position involves working closely with cross-functional teams to build predictive models that drive revenue growth. You will be responsible for translating data insights into actionable strategies that impact the company's B2B intelligence platform. The ideal candidate thrives in a collaborative environment and enjoys tackling ambiguous problems with data-driven solutions. You will have the opportunity to shape the direction of the company's analytics roadmap and influence product decisions at scale.

Key facts

What you'll do

• Design and implement machine learning models to improve customer targeting and scoring accuracy across the platform.
• Analyze large datasets to identify patterns and trends that inform product development and marketing strategies.
• Collaborate with engineering teams to deploy models into production environments and monitor their performance over time.
• Develop A/B testing frameworks to measure the impact of data-driven recommendations on business outcomes.
• Create data visualizations and reports that communicate findings to both technical and non-technical stakeholders.
• Mentor junior data scientists and contribute to the establishment of best practices within the team.
• Conduct exploratory data analysis to uncover new opportunities for improving the company's revenue intelligence capabilities.
• Work with product managers to define key metrics and success criteria for new feature development.
• Optimize existing algorithms and experiment with new approaches to enhance prediction accuracy and scalability.
• Participate in code reviews and contribute to the overall quality of the data science codebase.
• Lead cross-departmental initiatives to standardize data collection and modeling practices across the organization.
• Research emerging techniques in machine learning and recommend new methodologies that could benefit the platform.
• Evaluate model performance metrics and iterate on approaches to ensure continuous improvement of prediction quality.

Requirements

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of five years of professional experience in data science or a closely related discipline.
• Strong proficiency in Python and experience with machine learning libraries such as scikit-learn or TensorFlow.
• Demonstrated experience working with large-scale datasets and distributed computing frameworks like Spark or Hadoop.
• Solid understanding of statistical modeling, regression analysis, and classification techniques.
• Experience building and deploying machine learning models in production environments.
• Excellent communication skills with the ability to present complex findings clearly to diverse audiences.
• Familiarity with SQL and relational database systems for data extraction and manipulation tasks.
• Proven track record of delivering measurable business impact through data science projects.
• Ability to work independently and manage multiple projects with competing priorities in a fast-paced setting.
• Experience with big data technologies and distributed storage systems for handling high-volume data workloads.

Nice to have

• Advanced degree in a quantitative field such as a Master's or Ph.D. in Data Science or Statistics.
• Experience with cloud computing platforms including AWS, GCP, or Azure for data processing and model hosting.
• Background in B2B marketing technology or revenue intelligence solutions.
• Knowledge of deep learning frameworks and natural language processing techniques.
• Familiarity with MLOps practices and model versioning tools for maintaining production ML systems.

Skills & tools

• Python programming for data analysis, modeling, and automation tasks.
• SQL for querying and managing relational databases at scale.
• Machine learning frameworks including scikit-learn, TensorFlow, or PyTorch.
• Statistical analysis tools and techniques for hypothesis testing and experimentation.
• Data visualization libraries such as Matplotlib, Seaborn, or Plotly.
• Version control systems, particularly Git, for collaborative software development workflows.
• Experience with data pipeline tools and workflow orchestration platforms for end-to-end modeling.

Practical notes

• This role is based in the San Francisco office and requires on-site presence during standard business hours.
• The hiring process includes multiple interview rounds, including technical assessments and a team presentation component.
• 6sense offers competitive benefits packages that include health insurance, retirement planning, and professional development support.
• Candidates should be prepared to discuss past projects and demonstrate hands-on experience with machine learning workflows during interviews.
• The team values continuous learning and provides dedicated time for professional growth and skill development.