Data Specialist

Description

Key Responsibilities

• Able to translate product design requirements into pipeline of heuristic and stochastic algorithms
• Understand exploratory data analysis for product feasibility studies and ground truth testing
• Execute SQL queries and/or python scripts to manipulate, analyze and visualize data
• Able to implement explainable AI solutions and rationalize model inferences
• Follows SDLC processes, Adopt agile-based processes/meetings and peer code-reviews
• Works with Machine learning engineer/architect to deploy data products into production
• Follows and understands legal data use restrictions
• Contributes to algorithm library development and design for ML, NLP and XAI
• Delivers product pipelines for deployment to production
• Builds applications that integrate third party and self-hosted foundation models.
• Fine tunes open source foundation models (LLMs, VLMs) with proprietary data
• Develops autonomous AI inference and tool use orchestration using ReAct AI agents
• Provides root cause analysis for machine learning model inference
• Completes data analysis or processing tasks as directed
• Documents data product end to end design and development
• Data annotation, labeling and other related data generation activities
• Provides thought leadership for rest of team and seeks out opportunities to mentor more junior team members
• Presents and holds data product updates and trainings
• Updates team on data product performance

Education & Experience

• Strong problem solving skills with an emphasis on product development.
• 6+ years of experience developing data science products
• Strong experience using and optimizing common python machine and deep learning libraries such as Scikit learn, PyTorch, TensorFlow, Keras, MXNet and Spark MLlib
• Experience using statistical computer languages (Python, R, Scala, SQL, etc.) to manipulate data and draw insights from large data sets.
• Hands-on generative AI development Experience using foundation models (LLMs, VLMs)
• Experience with model fine tuning of open source foundation models with proprietary data
• Experience leveraging AI metrics for monitoring and value tracking
• Knowledge of AI Agent frameworks with recent hands-on experience building an AI agent able to autonomously use data stores, tools and other AI models to solve inquiries.
• Deep knowledge of data science concepts and related product development lifecycle
• Experience using machine learning libraries such as TensorFlow, Keras, SparkML etc.
• Working knowledge of machine learning tuning optimization procedures
• Experience working with and creating data architectures.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques. Preferred
• Experience with big data analytical frameworks such as Spark/PySpark
• Experience analyzing data from 3rd party providers: Google Knowledge Graph, Wikidata, etc.
• Experience visualizing/presenting data for stakeholders using: Looker, PowerBI, Tableau, etc.