Senior Data Scientist

• Lead the design, development, and deployment of advanced machine learning models and algorithms to solve complex business problems
• Provide technical leadership and mentorship to junior data scientists, fostering a culture of continuous learning and improvement
• Drive the strategic planning and execution of data science projects, ensuring alignment with business goals and timelines
• Collaborate with cross-functional teams, including engineering, product management and business stakeholders, to define project requirements and deliver data-driven solutions
• Conduct advanced exploratory data analysis (EDA) to uncover insights, trends, and patterns in large and complex datasets
• Develop and implement scalable data pipelines and workflows to support the end-to-end data science lifecycle
• Evaluate and integrate new data science techniques, tools, and technologies to enhance the company’s data capabilities
• Communicate complex analytical concepts and results to non-technical stakeholders through clear and compelling data visualizations and presentations
• Ensure the robustness, scalability, and performance of deployed models, monitoring their impact and iterating as necessary
• Champion best practices in data science, including data governance, model validation, and ethical AI considerations
• Identify and prioritize opportunities for leveraging data to drive business growth and operational efficiency
• Lead the development of custom machine learning models and algorithms tailored to specific business needs
• Stay current with the latest advancements in data science, machine learning, and AI, and apply this knowledge to drive innovation within the company
• Own team-level success by monitoring, modifying and creating team processes to help ensure consistency, continuity, efficiency and impact in analysis and ML pipelines
• Mentor and guide junior team members, sharing best practices and providing constructive feedback
• Pioneer peer reviews and foster a culture of continuous improvement and learning
• Develop and enforce data governance policies and procedures to ensure data integrity and security
• Monitor compliance with data privacy laws and regulations and implement measures to protect sensitive information

Data Science, Technical Leadership, Cross-Functional, Mentoring, Data Science, Project Planning, Strategic Planning, Product Programs, Technical Strategy, Business Support, * Bachelor’s Degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or Physics or a technical field (such as CIS or IT) relevant to the essential functions of this job description AND a minimum of 5 years of relevant experience OR an equivalent combination of education and relevant experience

• Excellent academics (cumulative GPA greater than or equal to 3.0 as a general rule)
• Extensive experience using systems such as SQL, Python, or R
• Strong expertise in machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
• Demonstrated expertise in advanced descriptive and inferential statistics, including the ability to apply these techniques to complex data sets and real-world problems
• Demonstrated expert knowledge in data analysis methods and tools
• Demonstrated strong and effective verbal, written, and interpersonal communication skills
• Must be team-oriented, possess a positive attitude, and work well with others
• Driven problem solver with proven success in solving difficult problems
• Consistently demonstrates quality and effectiveness in work documentation and organization

Desired Qualifications

• Advanced experience with structured database management systems and distributed computing
• Expertise in time series analysis, NLP, deep learning, or reinforcement learning
• Leadership in MLOps, model deployment, and CI/CD for data science workflows
• Advanced understanding of A/B testing and causal inference
• Experience working with unstructured data (text, images, audio, etc.)
• Advanced experience with data visualization tools (i.e. Matplotlib, Seaborn, Tableau)
• Proficiency with cloud platforms (e.g. AWS, Azure, GCP) for data science workflows
• Experience with real-time data processing technologies (e.g. Apache, Kafka)