Lead Data Scientist: Shape Strategy with Executives

Smith Arnold Partners

Scottsdale (AZ)

Hybrid

USD 140,000 - 200,000

Full time

14 days+

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Job summary

Smith Arnold Partners seeks a Lead Data Scientist in Scottsdale, AZ (Hybrid) to drive analytics from problem definition to implementation. You will partner with executives, develop predictive models, and translate results into strategic recommendations.

Ideal candidates have 10+ years in data science, strong Python/SQL, and experience communicating insights to C-suite stakeholders. This role offers ownership of high-impact projects and cross-functional collaboration.

Qualifications

10+ years of experience in Data Science, Predictive Analytics, Advanced Analytics, Quantitative Research, Risk Modeling, or related field.
3+ years hands-on experience developing ML models using Python.
Advanced SQL skills with experience querying and optimizing large datasets.
Strong foundation in statistics, predictive modeling, probability, sampling techniques, and experimental design.
Experience communicating analytical insights to executive stakeholders.
Ability to translate complex technical findings into practical business actions.
Strong project management and prioritization skills for multiple initiatives.
Proven ability to build credibility and influence with technical and non-technical stakeholders.

Responsibilities

Lead complex analytics initiatives from problem definition through implementation and measurement.
Partner with business leaders to identify opportunities and solve critical operational and strategic challenges.
Develop predictive models and machine learning solutions using large, complex datasets.
Create data-driven solutions related to customer retention, risk assessment, operational forecasting, and cost optimization.
Apply advanced analytical methods including supervised and unsupervised machine learning, regression analysis, forecasting, clustering, and classification techniques.
Gather, clean, validate, and integrate data from multiple internal and external sources.
Conduct statistical analysis, experimentation, back-testing, and quantitative research to validate findings.
Translate technical results into clear, compelling business recommendations for executive audiences.
Design dashboards, presentations, and analytical storytelling materials that influence decision-making.
Identify process improvement opportunities that reduce risk and improve operational performance.
Mentor and develop junior data scientists while elevating analytical practices.
Collaborate cross-functionally with operations, finance, technology, and executive leadership teams.