Lead - Data Scientist
First seen by Alion on Oct 23, 2026.
Key Responsibilities:
- Partner with business and technology leaders to identify high-value opportunities for applying data science and machine learning.
- Lead the design, development, and implementation of machine learning solutions aligned with business priorities.
- Own the end-to-end lifecycle of key data science initiatives, ensuring solutions are scalable, reliable, and suitable for real-world business use.
- Guide the selection of appropriate analytical approaches and evaluate solution effectiveness against business objectives.
- Drive the automation and standardization of analytical processes to improve operational efficiency and consistency.
- Establish practices for monitoring model performance, managing risks, and continuously improving deployed solutions.
- Work with data engineering, technology, and business teams to ensure seamless integration of analytical solutions into enterprise processes.
- Identify opportunities to improve business performance, decision quality, and operational efficiency through advanced analytics.
- Provide technical direction, review solution approaches, and mentor data scientists and other team members.
- Communicate complex analytical findings in a clear, business-oriented manner and influence decisions through data-driven recommendations.
- Promote best practices around data quality, model governance, responsible AI, and solution reliability.
- Contribute to the development of the team's capabilities, delivery standards, and long-term data science roadmap.
Required Skills & Experience:
- 8 - 10 years of experience in data science, machine learning, advanced analytics, or related fields.
- Strong hands-on experience in machine learning and statistical modelling, supported by proficiency in Python and SQL.
- Demonstrated experience leading the delivery of machine learning solutions from business problem definition through production implementation.
- Experience designing scalable analytical solutions and improving the performance and reliability of deployed models.
- Strong understanding of model lifecycle management, automation, monitoring, and governance.
- Proven ability to manage complex initiatives and work with multiple business and technology stakeholders.
- Experience mentoring team members and providing technical guidance.
- Strong communication, stakeholder management, analytical thinking, and decision-making skills.
Preferred Qualifications:
- Experience in banking, financial services, lending, credit risk, fraud detection, or other regulated industries.
- Exposure to cloud-based machine learning platforms and enterprise analytics ecosystems.
- Experience driving data science initiatives across multiple business functions or teams.
- Bachelor's or master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related discipline.
Skills
Data Science, Analytics, Machine Learning, Python, SQL, Statistics, Data Modeling, Data Scientist, Data Management