Note: The job is a remote job and is open to candidates in USA. Robots & Pencils is an applied AI engineering firm that designs and ships AI co-workers integrated into enterprise operations. The Staff Data Scientist will design scalable data science solutions, acquire and analyze data, build and validate statistical and machine learning models, and deploy generative AI systems. The role also involves customer engagement, cross-functional collaboration, executive communication, and mentoring other data scientists.
Responsibilities
- Design and implement scalable and reliable approaches to support or automate decision making throughout the business
- Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear
- Acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, RedShift, and Spark storage systems
- Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies
- Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks
- Validate models against alternative approaches, expected and observed outcomes, and other business defined key performance indicators
- Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production
- Implement and deploy state of the art machine learning algorithms under Gen AI, build prototypes, troubleshoot customer issues, and explore new solutions
- Interact closely with customers and with the academic community to drive innovation and deliver tailored data science solutions
- Build relationships with stakeholders and counterparts to understand business needs and translate them into data science solutions
- Collaborate closely with engineering, analytics, AI, and product teams to align data science models and insights with broader business goals
- Communicate findings and model results clearly to non-technical executive audiences, ensuring insights are actionable and understood
- Establish data science best practices and modeling standards that lift the quality and consistency of analytical work across the team
- Mentor junior and mid-level data scientists, helping them grow their craft, confidence, and impact
- Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to deliver higher-quality work at pace
Skills
- 10+ years of data scientist experience with a proven track record of solving complex business problems through data science
- Bachelor's degree and 8 years of experience or Master's degree and 4 years of experience
- 2+ years of hands-on experience with generative AI technology
- 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning (Will help Win Predictor Use case)
- 5+ years of hands on experience with Python to build, train, and evaluate models
- Customer facing experience
- Excellent communications skills with non-technical executive audiences, with the ability to translate complex models and findings into clear, actionable insights
- Competency in data querying languages (e.g. SQL) and scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
- Experience with statistical models (e.g., logistic regression, supervised learning approaches) and a solid foundation in machine learning methods
- Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor
- Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment
- Experience with advanced machine learning frameworks and cloud-based data science platforms is a plus
- Experience with handling and modeling data in the healthcare industry is a plus
- AWS certifications, like Certified Data Engineer – Associate, strongly preferred
- Masters or PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field
- Experience building generative AI applications on AWS using services such as Amazon Bedrock, Amazon Bedrock AgentCore and Amazon SageMaker
- Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches
- Experience with design, development, and optimization of high-quality prompts and templates that guide the behavior and responses of LLMs
- Experience with open source frameworks for building applications powered by LLMs like Strands, LangChain, LlamaIndex
- Hands on experience building cloud applications
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