Senior Data Scientist
$102,900.00 - $180,100.00
Apply (opens in a new tab)Senior Data Scientist
Posted 3 days ago
SENIORITY
Lead
SALARY
$102,900.00 - $180,100.00
About the role
- Lead the development of predictive models and machine learning solutions for business systems, asset management, sales, and commercial use cases.
- Apply regression, classification, segmentation, forecasting, clustering, and other statistical modeling techniques as appropriate.
- Explore, clean, transform, and analyze structured and unstructured data from multiple internal and external sources.
- Build repeatable data-mining processes, including data sourcing, data scraping where appropriate, feature engineering, modeling, validation, and evaluation.
- Use Python and data science libraries such as pandas, NumPy, scikit-learn, SciPy, Matplotlib, Seaborn, and Plotly.
- Develop, optimize, and maintain data models, dashboards, reports, and interactive decision-support tools.
- Design and improve data pipelines, database structures, APIs, data integrations, and analytical workflows.
- Support Digital Strategies activities using the Microsoft Azure technology stack; experience with Palantir Foundry is advantageous.
- Support long-term Sales Data Science initiatives, including model development, statistical analysis, forecasting, and performance measurement.
- Establish data-quality, validation, documentation, and governance practices to improve the reliability and responsible use of analytical products.
- Translate business questions into analytical approaches, explain results clearly, and make practical, actionable recommendations.
- Work closely with Federal clients, consulting teams, and multidisciplinary project groups.
- Contribute to workshops, technical discussions, requirements gathering, delivery planning, and client presentations.
- Document assumptions, methodologies, model performance, limitations, and recommendations to support responsible use of data science solutions.
- Review analytical methods, code, visualizations, and reports to ensure quality and alignment with project objectives.
- Lead analytical workstreams and provide mentoring and technical guidance to mid and junior analysts and data scientists.
- Contribute to proposals, business development activities, technical presentations, and reusable analytical solutions.
- Stay current with developments in data analytics, asset management, cloud technologies, artificial intelligence, and machine learning.
- Here's what you'll need
- Typically 5 or more years of experience in data science, advanced analytics, data analysis, business intelligence, or a related field.
- Demonstrated experience leading analytical projects or workstreams from requirements gathering through implementation, delivery, and client adoption.
- Bachelor's or Master's degree in Data Analytics, Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Asset Management, or a closely related discipline.
- Strong Python skills and practical experience with pandas, NumPy, scikit-learn, SciPy, and related data science libraries.
- Experience developing regression models, statistical models, segmentations, forecasting solutions, and machine learning applications.
- Strong understanding of statistics, exploratory data analysis, feature engineering, model evaluation, and performance measurement.
- Experience with data-mining processes, data preparation, data sourcing, and data scraping.
- Ability to work with messy, real-world business data and convert it into reliable and useful analytical outputs.
- Advanced proficiency with SQL and relational databases, including data modeling, transformations, joins, query optimization, and data validation.
- Experience developing dashboards, reports, and data visualizations using Power BI, Tableau, Matplotlib, Seaborn, Plotly, or comparable tools.
- Experience working with large, complex, and distributed datasets from multiple systems and sources.
- Experience with data pipelines, APIs, cloud data platforms, or enterprise data integrations.
- Experience working in consulting or client-facing delivery environments.
- Strong English communication skills and confidence working with all internal stakeholders, Federal clients, and nontechnical audiences.
- Ability to translate ambiguous business questions into structured analytical approaches and practical recommendations.
- Demonstrated ability to communicate technical concepts, analytical findings, assumptions, and limitations clearly.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
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A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
