Data Scientist Python/R Pr

Role Objective

Engineer to perform the design and development of advanced analytics, machine learning, and applied GenAI solutions that solve complex business problems across diverse client engagements.

Key Responsibilities

• Experience exploratory data analysis and hypothesis-driven modeling initiatives.
• Design, train, and validate machine learning models aligned with business objectives.
• Develop evaluation frameworks and define performance metrics.
• Prototype and validate GenAI use cases using LLMs and embeddings.
• Apply statistical rigor to experimentation and performance assessment.
• Communicate insights and recommendations to technical and business stakeholders.
• Collaborate with ML Engineers to productionize validated solutions.

Candidate Profile

• 3+ years of applied data science experience in enterprise environments.
• Experience designing multiagent solution, different generative frameworks, applying LLMs, embeddings, and prompt engineering techniques
• Strong statistical and modeling background.
• Expertise in Python and ML libraries..
• Ability to translate business needs into analytical solutions.
• Experience working in consulting or client-facing contexts preferred.
• Experience on some of the clouds (AWS, Azure or GCP).
• Advanced English proficiency.

Core Competencies

• Analytical rigor and structured problem-solving.
• Strong business acumen.
• Ability to operate in ambiguous and multi-industry environments.
• Clear communication and stakeholder management.

Indispensable

• Proven experience delivering GEN AI solutions in enterprise contexts.
• Strong statistical foundation and experimentation capability.
• Practical experience applying LLMs beyond theoretical exploration.
• Ability to connect analytical outcomes with measurable business impact.

DESEABLE

• Master's degree or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline.
• Proven Experience in Research and Analysis capabilities or Strong Research Background.
• Record of published research, technical papers, whitepapers, patents, or significant open-source contributions.