AI Data Scientist

Conga

. Research and evaluate emerging NLP, machine learning, deep learning, and Generative AI techniques .

Posted 10/16/2026full-timeHouston • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in NLP, Machine Learning, and Generative AI, with a strong focus on developing and deploying models from research to production. Proficient in experimental design, model evaluation, and optimization, ensuring high-quality data-driven solutions.

Highest-signal resume keywords

Expert-Level PythonNLP Solution DevelopmentDeep Learning ArchitecturesLLM and GenAI SolutionsStatistical Testing and Experimental Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NLP TechniquesMachine LearningDeep LearningTransformersSQLStatistical TestingHyperparameter OptimizationError AnalysisData ProcessingModel Evaluation Metrics

Soft Skills

Excellent CommunicationTechnical GuidanceCollaboration

Tools & Technologies

Hugging Face TransformersSpaCyPyTorchTensorFlowDatabricksAWSAzureDockerKubernetesFAISS

Certifications & Qualifications

Master's Degree in Computer ScienceMaster's Degree in Data ScienceMaster's Degree in Computational LinguisticsMaster's Degree in StatisticsMaster's Degree in MathematicsMaster's Degree in Engineering

Industry Keywords

Generative AIData ScienceModel DriftVector SearchRAGLLM EvaluationDistributed Data ProcessingCloud PlatformsML InfrastructureNLP Preprocessing

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudDockerElasticSearchGoogle Cloud PlatformKubernetesPythonPyTorchRaySparkSQLTensorflow

About the role

Key responsibilities & impact

Research and evaluate emerging NLP, machine learning, deep learning, and Generative AI techniques
Investigate ambiguous technical problems, form hypotheses, and run comparative experiments
Evaluate models, frameworks, and methodologies and adopt improvements to product capabilities and system performance
Design and build traditional NLP, statistical ML, deep learning, and transformer-based solutions
Develop data pipelines, NLP preprocessing, feature representations, embeddings, and training datasets
Establish data-quality strategies for reliable models
Develop and evaluate LLM and GenAI solutions using prompting, RAG, embeddings, vector search, fine-tuning, agents, and structured generation
Select and optimize models based on accuracy, latency, cost, and business requirements
Define how Conga builds, grounds, and governs GenAI capabilities
Design experiments, benchmarks, evaluation datasets, and statistical methodologies
Lead error analysis and performance measurement
Set evaluation standards for the broader team
Take AI solutions from research and prototype through production deployment, monitoring, and optimization
Partner with engineering teams to operationalize models at scale
Identify model drift, quality gaps, and optimization opportunities
Collaborate with engineering, product, and data science teams
Provide technical guidance and mentorship in NLP, ML, experimentation, and GenAI

Requirements

What you’ll need

Master's degree in Computer Science, Data Science, Computational Linguistics, Statistics, Mathematics, Engineering, or a related quantitative field
10+ years of professional experience in data science, machine learning, NLP, or AI, including significant hands-on experience building and deploying NLP and/or GenAI solutions
Proven experience taking ML, NLP, or GenAI solutions from experimentation through production deployment and ongoing optimization
Demonstrated ability to translate open-ended research into practical, measurable outcomes
Excellent communication skills and experience working as a senior individual contributor across technical teams
Expert-level Python with extensive use of Hugging Face Transformers, spaCy, NLTK, Sentence Transformers, PyTorch, and TensorFlow
Expert knowledge of traditional NLP techniques
Strong understanding of deep learning architectures and Transformer-based language models
Hands-on experience with LLMs and foundation models, including prompt engineering, RAG, vector search, reranking, fine-tuning, LoRA/QLoRA, structured generation, and LLM evaluation
Strong grasp of experimental design, statistical testing, cross-validation, hyperparameter optimization, and error analysis
Experience with NLP and GenAI evaluation metrics
Strong SQL skills and experience with structured and unstructured data at scale
Experience with distributed data processing platforms such as Spark, Databricks, or BigQuery
Experience with cloud platforms such as Databricks, GCP, AWS, or Azure and modern ML infrastructure
Experience with ML tooling such as MLflow, Kubeflow, Weights & Biases, Docker, Kubernetes, or Ray
Experience with vector databases and search technologies such as FAISS, Elasticsearch/OpenSearch, Pinecone, Weaviate, or Milvus
Familiarity with LLM application frameworks such as LangChain, LlamaIndex, or DSPy

Benefits

Comp & perks

Individual and team development opportunities
Equal employment opportunities
Reasonable accommodation for applicants with disabilities
Limited travel to other Conga offices upon request