Data Scientist Senior

Accountabilities: Analyze large and complex datasets to solve unstructured business problems using statistical analysis, econometrics, and machine learning techniques.

Source, ingest, clean, transform, and prepare data for analysis while supporting reliable, scalable, and high-quality data pipelines.

Design, develop, validate, and implement advanced analytical models, including classification, clustering, pattern analysis, sampling, simulations, and predictive modeling.

Build champion/challenger models and continuously refine model performance based on accuracy, reliability, stability, and business feedback.

Develop self-healing model frameworks and support the deployment and productionization of machine learning models in enterprise environments.

Apply statistical and data engineering techniques using SQL, Python, Alteryx, Tableau, Power BI, and related analytical tools.

Create model outputs, visualizations, reports, and educational materials that clearly communicate analytical findings and business value to stakeholders.

Collaborate with senior data scientists, business partners, and technical teams to establish research approaches and tailor analytical methods to business and client requirements.

Review code for accuracy, efficiency, maintainability, quality, and compliance with development best practices.

Provide technical guidance and mentorship to less experienced team members, helping them develop reliable, consumable data products and model outputs.

Participate in stakeholder discussions to explain results, identify analytical opportunities, address concerns, and resolve production challenges.

Monitor data quality, model stability, and scalability across on-premises and cloud-based environments.

Identify and escalate risk-related issues while adhering to applicable regulatory requirements, audit standards, internal controls, and risk management policies.

Requirements:

Bachelor's degree and at least five years of relevant professional experience, or a combination of higher education and work experience totaling at least nine years, including a minimum of five years of related experience.

At least five years of experience in data science, statistics, econometrics, quantitative analysis, or a related discipline.

Demonstrated experience working with large, complex, and diverse datasets.

Strong understanding of statistical and data science principles, including A/B testing, sample selection, hypothesis testing, model validation, and bias analysis.

Proficiency in statistical software, programming languages, and analytical tools used for data exploration, modeling, and reporting.

Intermediate knowledge of SQL and NoSQL databases, with practical experience performing data extraction, transformation, and loading (ETL) using SQL and Python.

Experience working with hybrid database environments spanning on-premises infrastructure and cloud platforms.

Familiarity with advanced modeling methods, including Bayesian modeling, classification, clustering, neural networks, non-parametric techniques, and multivariate statistics.

Experience creating data visualizations and communicating analytical insights using Tableau and Power BI.

Hands-on experience with Alteryx.

Excellent written and verbal English communication skills, with the ability to explain technical findings clearly and collaborate professionally with diverse stakeholders.

Strong analytical thinking, problem-solving, attention to detail, and the ability to work independently on complex initiatives.

Preferred qualifications: A master's degree or doctorate in Statistics, Economics, Finance, or another quantitative discipline; advanced knowledge of econometric methods such as time-series analysis, panel data techniques, and logistic regression; and experience developing and deploying machine learning models in enterprise production environments.

Benefits:

Expected base salary of $43.06–$71.76 per hour , depending on relevant skills, training, experience, education, market factors, and applicable licenses or certifications.

Competitive benefits package in addition to base compensation.

Fully remote work arrangement.

Six-month contract engagement.

Opportunity to work on complex data science and machine learning initiatives using modern analytical tools and technologies.

Opportunities to provide technical mentorship and collaborate with experienced data science, business, and technology professionals.

Equal employment opportunity in accordance with applicable laws and regulations.

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