Define a data science strategy in support of the overall business strategy and objectives and execute against it.
Identify new opportunities for leveraging data and advanced analytics to solve complex business problems and drive growth.
Recruit (as needed), mentor, and develop a team of talented data scientists, machine learning engineers, and data analysts. Direct reports may include other Sr. Managers and/or Managers.
Foster a culture of innovation, continuous learning, and data-driven decision-making within.
Oversee the design, development, and deployment of predictive models, machine learning algorithms, and other advanced analytical solutions.
Identify and prioritize AI-enabled features for our existing solutions (e.g., predictive analytics, intelligent automation, personalized recommendations, natural language processing).
Ensure the accuracy, reliability, interpretability and usability of data science outputs.
Collaborate closely with engineering, product, and business stakeholders to understand needs and translate them into data science initiatives.
Communicate complex analytical insights clearly and concisely to diverse audiences at all levels of the organization.
Help foster AI experimentation and diffusion across the organization.
Establish and enforce best practices for data quality, data governance, and model lifecycle management.
Stay abreast of industry trends and emerging technologies in data science and machine learning.
Requirements
Education: A Master's or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Quantitative Economics, or a related quantitative field.
Experience:
7+ years of hands-on experience in a data science or machine learning role.
3+ years of experience in a leadership or management position, with a proven track record of building and mentoring data science teams.
Demonstrated experience in shipping AI-enabled products to market, with a focus on both new product development and feature augmentation of existing software.
Technical Skills:
Expertise in a programming language such as Python (including libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch) or R.
Strong background in machine learning techniques, statistical modeling, and experimental design (A/B testing).
Strong experience in model building, fine-tuning, RAG, and other latest methodologies in AI technologies.
Proficiency in SQL for data extraction and manipulation.
Experience with big data technologies and cloud platforms (AWS, Azure, or GCP).
Benefits
Medical, dental, and vision insurance
401k with employer match
Flexible Time Off Policy, with 10 company paid holidays
2 days of volunteer time off
12–15 weeks of paid parental leave, with eligibility based on tenure and in alignment with FMLA guidelines
Fully remote, in-office, or hybrid work environment
Monthly home internet stipend
Employee support groups, social groups, and mentorship program
Employee-driven programs for volunteering
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data science strategymachine learningpredictive modelingstatistical modelingexperimental designPythonRSQLbig data technologiesAI technologies