Senior Data Scientist
Removed from the employer's board on Nov 5, 2026. First seen by Alion on Nov 3, 2026.
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Job title : Senior Data Scientist
Location: : Dallas, TX (onsite)
Duration: 12+months
Experience: 12+ years
Mode of interview: F2F
Visa: No OPT/CPT EAD
- Role Overview
This is a senior-level Data Scientist position requiring a strong combination of:
- Hands-on Data Science
- Machine Learning
- Strong coding/programming ability
- Business problem solving
- Consulting and stakeholder-management skills
- Ability to translate business requirements into analytics or machine-learning problems
- Independent end-to-end ownership of use cases
The manager is specifically looking for someone who is not just technically strong, but can work directly with business partners, understand their problems, and translate those problems into practical data science solutions.
- Technical Skills Required
Data Science
This is the fundamental requirement. Candidates should have substantial hands-on experience solving real business problems using data science.
The person needs to be capable of independently working through a problem rather than only executing predefined technical tasks.
Machine Learning
Machine Learning experience appears to be strongly preferred, although the discussion indicated that a candidate without ML experience could still potentially be considered.
However, because only the top five candidates will be shortlisted, candidates possessing both Data Science and Machine Learning experience will have an advantage.
Coding
Candidates must have solid hands-on coding skills.
Coding is expected to represent roughly half of the role's responsibilities, while the other half centers on interacting with business partners, consulting, and translating business problems into analytical solutions.
An important point is that coding skills will be assessed during the onsite interview through a whiteboard exercise.
- Business & Consulting Skills
This appears to be one of the most important clarifications from the hiring manager.
The successful candidate cannot be purely a technical Data Scientist.
They need to work directly with business partners and function partly as an internal consultant.
Key expectations include:
- Understand business problems and objectives.
- Communicate directly with business stakeholders.
- Ask the right questions to properly define the problem.
- Translate business problems into clearly defined analytics or Machine Learning problems.
- Recommend appropriate scientific/analytical approaches.
- Explain technical concepts and solutions to business stakeholders.
- Combine technical analysis with practical business problem solving.
This area appears to have been a gap with at least one previously interviewed candidate. The candidate reportedly performed reasonably well technically but was not strong enough in the business-partner interaction portion of the position.
Therefore, stakeholder-facing consulting experience should be treated as a major screening criterion, not a soft skill.
- End-to-End Ownership
The manager is looking for someone who can independently own a use case or business problem.
Based on the discussion, the candidate should be able to:
Business problem Define the problem Identify/find the required data Perform feature engineering Develop the analytical/ML solution
The expectation is that the individual should not require someone else to completely define the problem or prepare everything before they begin technical work.
The candidate should demonstrate examples where they personally took ownership of a problem and drove it through the Data Science lifecycle.