Sr. Data Scientist in Dallas, Texas(Hybrid)
Why This Role Stands Out
This Sr. Data Scientist role offers a fantastic opportunity to leverage your advanced analytical skills within a reputable consulting firm, fostering significant career growth and skill development in a hybrid Dallas-based environment. If you thrive on complex problem-solving and contributing to impactful projects, this position is an excellent next step for your career journey.
Quick Overview
Job Description
Title: Sr. Data Scientist
Location: Dallas, Texas
Duration: 6 to 12 Months
Hybrid Position - 3 Days Onsite (Tue, Wed, Thu)
Final Round In Person Interview Mandatory
Experience in Operational research environment is mandatory
Job Description:
7+ years of experience required
Top 3 Mandatory Skills and Experience:
- Proficient in Python
- Experience/knowledge on designing and implementing Gen AI applications- Hands-on experience with Machine Learning and AI pipeline build, model deployment, orchestration, monitoring, and optimization.
- Experience in Operational research environment is mandatory.
Nice to Have Skills:
- Microsoft Dynamics
- Prompt Engineering
- Proficiency in SQL and working with data
- Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
Description:
Minimum Qualifications – Education & Prior Job Experience
- Master or PhD degree with 5+ years of experience in quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.)
- Python proficiency (production-grade coding, modularization, testing, performance tuning)
- Hands on experience with building Gen AI applications – prompt engineering, classifiers, knowledge bases, RAG solutions, LLMs as judges, etc.
- Hands-on experience with ML/AI pipeline development and productionization (model deployment, orchestration, monitoring, and optimization)
- Depth of knowledge in statistical and machine learning techniques
Preferred qualifications – Education & Prior Job Experience
- Experience with Azure ML, Databricks
- Proficiency in SQL and working with data
- Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
- Practical experience designing, building and deploying machine learning models
- Domain knowledge in the airline industry
- Experience working in a consulting role
Skills, Licenses & Certifications
- Ability to effectively communicate both verbally and written with all levels within the organization
- Demonstrated motivation and aptitude for logical analysis, problem identification, and problem solving
- Ability to view data from different angles to employ feature engineering techniques to better represent models
- Ability to work on a diverse team with diverse skillsets
- 7 years of experience required
Describe a great candidate that you are looking for and what skills and experience they will have:
- Has experience with LLMs and Agentic AI
- Has experience building customer facing Gen AI applications; awareness on guardrails, privacy, cybersecurity concerns
- Has proven experience taking ML models from prototype to production with Python and Azure ML; containerize where needed.
- Demonstrated strong skills in code optimization, debugging, and system integration.
- Understands end-to-end ML lifecycle, including deployment and monitoring.
- Is comfortable working with existing codebases and improving them, as well as building new ones from scratch. Clear communication and effective collaboration.
What is the team environment and structure like?:
- ML/AI team supporting Contact Centers and Digital Customer Experience
- Will collaborate with several team members
- Collaborative, supportive, and high-performing culture
- Strong focus on quality, innovation, scalability, and measurable revenue impact
How will the resource fit into your team?:
- The resource will be embedded within the team and support the Service Recovery Modernization initiative.
- Take ownership of data preparation, data pipelines, design, test, and deployment of ML and Gen AI applications.
- Collaborate closely with data scientists, data engineers, and product partners.
- Accelerate delivery of scalable, production-ready AI solutions.
Skills
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