Note: The job is a remote job and is open to candidates in USA. ECCO Select is a talent acquisition and consulting company specializing in people, process and technology solutions. They are seeking a Senior Data Scientist to establish and grow an AI/ML innovation lab, focusing on designing, developing, and deploying advanced AI and machine learning solutions, particularly in generative AI.
Responsibilities
- Lead research, prototyping, and end-to-end development of AI/ML solutions, with particular attention to generative AI use cases
- Design, build, and iterate on proof-of-concept applications to demonstrate value and translate these prototypes into scalable, production-ready systems
- Develop large language model applications to support tasks such as text analysis, summarization, information extraction, document classification, and workflow automation
- Experiment with, fine-tune, and evaluate AI models, incorporating prompt engineering and retrieval-augmented generation to improve outcomes
- Evaluate, recommend, and pilot emerging AI technologies, tools, frameworks, and models for adoption by the organization
- Apply classical and modern ML techniques, including supervised/unsupervised learning, regression, classification, NLP, and deep learning
- Lead deployment and monitoring of models across cloud, containerized, and internal environments, managing the full application lifecycle from initial release through maintenance and updates
- Create interactive dashboards and analytical applications using Python or R frameworks (such as Streamlit, Dash, Flask, and R Shiny) to communicate insights and support decision making
- Translate complex analytics into actionable insights for non-technical stakeholders, designing intuitive visualizations and presenting technical findings in accessible terms
- Manage deployment pipelines, including containerization (Docker), CI/CD, API integrations, rate limiting, and cloud cost management
- Implement monitoring, logging, alerting, and dashboarding for application and model performance, quality, and system health
- Establish and maintain documentation for technical, security, privacy, compliance, and production-readiness requirements
- Participate in agile team practices, including sprint planning, daily standups, and retrospectives, while communicating progress and managing risks across multidisciplinary teams
- Engage directly with both technical and non-technical stakeholders, including analysts, legal, technology staff, and senior leaders, to understand business needs and identify practical AI opportunities
- Champion responsible AI practices, including fairness, bias detection, explainability, and compliance with privacy and security requirements in regulated settings
- Collaborate with, or independently manage, cloud and infrastructure engineering tasks as needed for end-to-end solution ownership
- Contribute to the development of documentation, best practices, and mentoring to build internal AI/ML capabilities
Skills
- U.S. Citizenship required
- Bachelor's degree in Computer Science, Data Science, Statistics, Machine Learning, or related field
- 6+ years of hands-on experience developing, deploying, and maintaining AI/ML solutions in enterprise, academic, government, or similarly complex environments
- Advanced proficiency with Python or R for data science and application development, with additional programming language experience preferred
- Experience building and maintaining AI/ML applications in cloud production settings
- Hands-on experience with containerization (Docker) and foundational knowledge of CI/CD practices
- Proficient in building interactive applications and dashboards with frameworks such as Streamlit, Dash, Flask, or R Shiny
- Strong background in developing sophisticated data visualizations using Plotly, Matplotlib, Seaborn, ggplot2, Tableau, Power BI, or equivalent tools
- Deep expertise in machine learning, natural language processing, and generative AI technologies, including LLMs and NLP pipelines (e.g., text normalization, entity recognition, word embeddings)
- Experience with key AI/ML libraries such as Scikit-learn, spaCy, XGBoost, and related technologies
- Expertise in statistical modeling, data analysis, and applied analytical problem solving
- Demonstrated ability to independently deliver solutions from initial concept and research through to deployment and long-term maintenance
- Outstanding written and verbal communication skills, with the capability to distill complex concepts for technical and lay audiences alike
- Experience working within or alongside federally regulated IT governance processes, including security, privacy, and compliance
- Ability to manage through ambiguity, adapt to evolving requirements, and contribute to team-based agile workflows
- Master's degree in a relevant technical field strongly preferred
- Prior experience supporting U.S. federal government or regulatory bodies
- Experience in financial services data, compliance, or regulatory analytics valued
- Proficiency working in agile environments, such as Scrum or Kanban, and experience with tracking tools like Jira or Azure DevOps
- Hands-on experience with large language model APIs (e.g., GPT, Llama) and generative AI frameworks (e.g., LangChain, LlamaIndex)
- Knowledge of prompt engineering, model fine-tuning, vector databases, and retrieval-augmented generation techniques
- Familiarity with AWS AI services (e.g., Bedrock, SageMaker, Comprehend, Rekognition, Transcribe), as well as AWS infrastructure (EC2, ECS, Lambda, S3, CloudWatch)
- Experience using infrastructure-as-code solutions such as Terraform or CloudFormation
- Relevant AWS certifications and experience with Databricks, MLOps practices, and multi-modal AI development are a plus
- Demonstrated commitment to responsible AI standards, bias mitigation, model transparency, and data governance in sensitive environments
- Familiarity with FISMA, federal privacy, security, and governance frameworks
Company Overview