Senior Data Scientist – Machine Learning & GenAI

Job Title: Senior Data Scientist – Machine Learning & GenAI - USA

Industry: Data Science / Machine Learning / Generative AI

Location: Houston, Texas, USA

Salary: USD 125,000–150,000 per annum per annum + Benefits

Work Authorization: US Citizens, Green Card holders and candidates with valid H-1B status

About the Role

We are seeking an experienced Senior Data Scientist – Machine Learning & GenAI with a strong foundation in traditional machine learning and data science, complemented by hands-on experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and agentic AI workflows.

This is a highly applied role requiring someone who has built and implemented data science and AI solutions in real-world commercial or enterprise environments. We are particularly interested in candidates who combine strong technical capability with the confidence to engage directly with customers and work effectively across product and engineering teams.

The successful candidate should not be purely academic or research-focused. Practical implementation experience, commercial awareness and strong communication skills are essential.

Key Responsibilities

• Design, develop and deploy machine learning and statistical models to solve complex business problems.
• Develop practical Generative AI and LLM-based solutions, including RAG architectures and agentic AI workflows.
• Analyse large and complex datasets to identify trends, patterns and actionable business insights.
• Build predictive and analytical models that support product development and data-driven decision-making.
• Work closely with product managers, engineers and other stakeholders to integrate machine learning and GenAI capabilities into enterprise products and services.
• Translate customer and business requirements into scalable data science and AI solutions.
• Participate confidently in customer-facing discussions, communicating technical concepts, findings and recommendations to both technical and non-technical audiences.
• Evaluate and improve model performance, reliability and business impact.
• Provide guidance and mentorship to junior data scientists where appropriate.
• Keep abreast of developments in machine learning, Generative AI, LLMs and related technologies.

Required Experience & Skills

• 7–15 years of relevant professional experience in data science, machine learning or a closely related discipline.
• Strong hands-on experience with traditional machine learning algorithms, predictive modelling and statistical techniques.
• Practical experience developing and implementing Generative AI and LLM-based applications.
• Hands-on knowledge of Retrieval-Augmented Generation (RAG) architectures and implementation.
• Experience with agentic AI or agent-based workflows.
• Strong proficiency in Python and/or R, including relevant data manipulation and machine learning libraries.
• Experience with frameworks such as Scikit-learn, PyTorch and/or TensorFlow.
• Strong SQL skills and experience working with large datasets.
• Experience with big-data technologies such as Spark, Hadoop or comparable platforms.
• Experience taking machine learning or AI solutions beyond experimentation into practical implementation or production.
• Strong analytical and problem-solving capabilities.
• Excellent written and verbal communication skills.
• Ability to engage confidently with customers and explain complex technical concepts to non-technical stakeholders.
• Proven ability to collaborate effectively with engineering, product and business teams.

Preferred Qualifications

• Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Engineering or another relevant quantitative discipline.
• Experience developing data science or AI capabilities for enterprise products or platforms.
• Experience deploying ML and GenAI solutions into production environments.
• Familiarity with cloud platforms such as AWS, Microsoft Azure or Google Cloud Platform.
• Experience with data visualisation or business intelligence tools such as Tableau or Power BI.
• Previous customer-facing, consulting or product-oriented experience.
• Experience mentoring or technically guiding junior data scientists.

What We Are Looking For

The ideal candidate will combine three important dimensions:

Strong Machine Learning Foundation
You should have substantial experience in traditional data science, statistical modelling, predictive analytics and machine learning. GenAI experience alone will not be sufficient.

Practical GenAI Capability
You should be able to demonstrate hands-on experience building or implementing LLM applications, RAG solutions and/or agentic AI workflows for genuine business use cases.

Commercial & Customer Engagement
You should be comfortable working beyond the technical environment, engaging with customers, understanding business requirements and explaining sophisticated AI and data science solutions clearly.

Candidates should ideally be able to discuss specific examples of models or AI solutions they have developed, how these were implemented, the business problem addressed and the resulting impact.

Working Environment

You will work within a collaborative, product-focused environment alongside data scientists, engineers, analysts and product professionals developing innovative AI and data-driven solutions for enterprise customers.

The environment places a strong emphasis on practical implementation, collaboration, continuous learning and measurable business outcomes, providing an opportunity to work at the intersection of established machine learning techniques and emerging Generative AI technologies.