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Lead Data Scientist

• Posted 2 hours ago • Updated 2 hours ago

Full Time

Fitment

Dice Job Match Score™

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Job Details

Skills

Continuous Improvement
Mentorship
Regression Analysis
Clustering
Time Series
Data Analysis
Data Quality
Collaboration
Statistics
Mathematics
Computer Science
Economics
Operations Research
Data Science
Advanced Analytics
Machine Learning (ML)
Analytical Skill
Python
R
Modeling
SQL
Forecasting
Optimization
Pricing
Customer Analysis
Generative Artificial Intelligence (AI)
Large Language Models (LLMs)
Artificial Intelligence
Analytics

Continuous Improvement
Mentorship
Regression Analysis
Clustering
Time Series
Data Analysis
Data Quality
Collaboration
Statistics
Mathematics
Computer Science
Economics
Operations Research
Data Science
Advanced Analytics
Machine Learning (ML)
Analytical Skill
Python
R
Modeling
SQL
Forecasting
Optimization
Pricing
Customer Analysis
Generative Artificial Intelligence (AI)
Large Language Models (LLMs)
Artificial Intelligence
Analytics

Summary

Job Description

The Lead Data Scientist is responsible for developing, implementing, and scaling advanced analytics, machine learning, and artificial intelligence solutions that drive business value. This role partners closely with cross-functional stakeholders to translate complex business challenges into data-driven insights and predictive solutions.

The Lead Data Scientist owns the end-to-end lifecycle of data science initiatives, from opportunity identification and model development through deployment, monitoring, and continuous improvement. This role also contributes to the advancement of data science capabilities by establishing best practices, mentoring team members, and promoting analytical excellence across the organization.

Responsibilities

Essential Duties and Responsibilities:

Design, develop, and implement statistical, machine learning, forecasting, optimization, and predictive models.
Apply advanced analytical techniques, including regression, classification, clustering, time series analysis, anomaly detection, and other quantitative methods.
Translate business challenges into scalable analytical solutions that generate measurable business outcomes.
Conduct exploratory data analysis to identify trends, patterns, opportunities, and risks.
Assess data quality, completeness, and suitability for analytical and modeling initiatives.
Design, develop, and validate features that improve model performance and business relevance.
Lead the full lifecycle of data science solutions, from problem definition and model development through deployment and ongoing optimization.
Evaluate model performance, accuracy, stability, reliability, and business impact.
Partner with engineering and technology teams to deploy and operationalize models within business Collaborate with business leaders and stakeholders to define objectives, key metrics, constraints, and success criteria.
Identify and prioritize high-impact opportunities where data science can improve business performance.
Communicate analytical findings, recommendations, assumptions, and risks to both technical and non-technical audiences.
Ensure solutions are actionable, interpretable, and aligned with business needs and strategic objectives.

Qualifications

Minimum Education and/or Experience:

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related quantitative field required.
Advanced degree in a quantitative field (preferred)
7+ years of progressive experience in data science, machine learning, advanced analytics, or a related field.
Demonstrated experience developing, deploying, and supporting predictive and machine learning models in production environments.
Experience leading complex analytical initiatives from problem definition through adoption
Strong proficiency in Python and/or R for modeling and production-quality code
Strong SQL skills for data exploration and dataset development
Experience with forecasting, optimization, pricing, customer analytics, operational analytics, or related business applications.
Familiarity with generative AI, large language models (LLMs), and emerging AI technologies.
Experience working in cross-functional environments (engineering, analytics, business teams)
Ability to communicate complex concepts to non-technical stakeholders

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 80183831
Position Id: 1654a9e4369ea1c4e939bf076de33f87
Posted 2 hours ago

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