Senior Data Scientist

About the Role
We are seeking an accomplished Senior Data Scientist with a minimum of 7 years of professional experience to develop advanced machine learning solutions, predictive models, and AI-driven analytical capabilities within a large-scale enterprise technology environment.
This position offers the opportunity to work on complex business challenges involving Machine Learning (ML), Artificial Intelligence (AI), Generative AI, Large Language Models (LLMs), Predictive Analytics, Statistical Modeling, Natural Language Processing (NLP), and Advanced Data Analytics.
The Senior Data Scientist will collaborate with Data Engineering, Machine Learning Engineering, Product Management, Software Engineering, and business leadership to transform complex datasets into actionable intelligence and scalable AI solutions.
The ideal candidate combines advanced quantitative expertise, strong programming capabilities, experience deploying machine learning models, and the ability to translate sophisticated analytical findings into measurable business outcomes.
Essential Duties and Responsibilities
Design, develop, validate, and optimize advanced machine learning and statistical models.
Apply supervised and unsupervised learning techniques to solve complex business problems.
Develop predictive models for forecasting, classification, regression, recommendation systems, and anomaly detection.
Perform exploratory data analysis, feature engineering, data preparation, and model evaluation using Python, SQL, and modern machine learning frameworks.
Develop and evaluate Generative AI, NLP, and LLM-based solutions where appropriate.
Design and analyze A/B tests, statistical experiments, and causal inference studies.
Collaborate with ML Engineers to deploy scalable machine learning models into production environments.
Improve model accuracy, explainability, reliability, and computational efficiency.
Establish model monitoring practices to identify performance degradation, data drift, and emerging risks.
Develop reusable analytical frameworks and production-ready data science workflows.
Communicate technical findings, analytical insights, and recommendations to executive and cross-functional stakeholders.
Provide technical mentorship and guidance to Data Scientists and analytical team members.
Job Qualifications and Requirements
Minimum 7 years of professional experience in Data Science, Machine Learning, Applied Statistics, or a closely related quantitative field required.
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline, or equivalent practical experience.
Master's degree or PhD in a relevant discipline is preferred.
Advanced proficiency in Python and SQL.
Strong experience with machine learning libraries including scikit-learn, XGBoost, TensorFlow, PyTorch, or equivalent frameworks.
Advanced understanding of statistical analysis, probability, hypothesis testing, regression, classification, and experimental design.
Hands-on experience building, validating, and deploying machine learning models.
Experience working with large-scale structured and unstructured datasets.
Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Experience with Databricks, Snowflake, Apache Spark, or comparable enterprise data platforms.
Understanding of MLOps, MLflow, model monitoring, CI/CD, and production machine learning workflows.
Familiarity with Generative AI, Large Language Models, Retrieval-Augmented Generation (RAG), vector databases, or NLP is advantageous.
Experience translating complex analytical results into business recommendations.
Strong written and verbal communication skills.
Personal Capabilities and Qualifications
Exceptional analytical reasoning and advanced problem-solving capabilities.
Strong mathematical and statistical judgment.
Ability to independently investigate complex and ambiguous business problems.
High standards for model quality, reproducibility, and analytical accuracy.
Ability to balance technical sophistication with practical business value.
Strong ownership of analytical solutions and measurable outcomes.
Excellent communication with technical and nontechnical stakeholders.
Ability to mentor colleagues and provide constructive technical guidance.
Effective collaboration within distributed and remote teams.
Intellectual curiosity about emerging AI technologies and evolving data science methodologies.
Strategic Support
Contribute technical expertise to enterprise AI and advanced analytics strategies.
Identify opportunities to apply machine learning to business growth, operational efficiency, and customer experience.
Support responsible adoption of Generative AI and intelligent automation.
Provide analytical guidance for high-impact product and business decisions.
Help establish scalable and reusable machine learning capabilities.
Contribute to model governance, explainability, fairness, privacy, and responsible AI practices.
Support long-term data science innovation and technology modernization initiatives.
Working Conditions
100% Remote position within the United States.
Full-time position within a large enterprise technology environment.
Regular virtual collaboration with Data Science, AI/ML Engineering, Data Engineering, Product, Technology, and business teams.
Collaboration across multiple U.S. time zones may be required.
Occasional participation in model deployment, production investigations, or critical analytical initiatives may be necessary.
Responsible handling of confidential, proprietary, customer, and enterprise information is required.
Job Function
Primary Function: Data Science & Artificial Intelligence
Specialization: Advanced Machine Learning, Predictive Analytics & Applied AI
Workplace: Remote — United States
Employment Type: Full-Time
Experience Required: Minimum 7 Years
Relevant Skills & Keywords: Senior Data Scientist, Data Science, Machine Learning, Artificial Intelligence, Applied AI, Generative AI, Predictive Modeling, Statistical Modeling, Python, SQL, Deep Learning, Natural Language Processing, NLP, Large Language Models, LLMs, Retrieval-Augmented Generation, RAG, Feature Engineering, A/B Testing, Causal Inference, Experimentation, Forecasting, Recommendation Systems, XGBoost, scikit-learn, TensorFlow, PyTorch, AWS, Azure, GCP, Databricks, Snowflake, Apache Spark, MLOps, MLflow, Model Deployment, Model Monitoring, Data Analytics, AI Model Evaluation.
Compensation & Benefits
We offer a competitive compensation package based on professional experience, technical expertise, qualifications, geographic location, and overall position responsibilities.
The total rewards package may include:
Competitive annual base salary
Performance-based annual incentives
Equity or long-term incentive opportunities where applicable
Medical, dental, and vision insurance
Retirement savings plans with employer contributions
Paid time off and company holidays
Paid parental and family leave
Life and disability insurance
Remote-work support and equipment assistance
Professional development and advanced technical training
AI, machine learning, and cloud certification opportunities
Wellness and employee-assistance programs
Additional benefits according to company policy
Why Join Us
Join a large-scale enterprise technology environment where Data Science, Machine Learning, and Artificial Intelligence play an important role in shaping digital innovation, customer experiences, and business decisions.
You will have opportunities to work with complex datasets, modern cloud platforms, advanced AI technologies, and experienced technical professionals while developing solutions with measurable enterprise impact.
This posit

Work arrangement
Yes