84 applicants

Company

HAND (Human & Digital) · 17 hours ago

AI Data Scientist for Predictive Analytics / BI Identity platform - co-founder role

United States

Full-time

Remote

Senior Level

5+ years exp

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Hiring Manager

Will Kreth

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Responsibilities

Develop valuable capabilities in Predictive Analytics and Business Intelligence

Utilize data science, statistics, data analytics, data visualization, and data analysis to support the development of the platform

Lead and collaborate in the creation of the business intelligence and predictive analytics arm, Handlytics

Translate past successes into systems and technologies with a focus on combining breakthroughs in Generative AI functionalities with advanced knowledge graphs and applied semantic models

Create an event-driven, API-centric, cloud-native data/processing, elastically scaling, highly-visual interactive SaaS analytics application.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Computer Science DegreeData Science DegreeLLM ExpertiseGenerative AINLP TechniquesData VisualizationNeural Network LibrariesGraph DB SolutionsDatabase TechnologiesKnowledge RepresentationMachine LearningGraphQL APIsREST APIsPythonAgile MethodologiesJiraConfluenceJavaJavaScriptScalaTableauSplunkCloud Identity ManagementAWS Cloud PractitionerCustomer-Centric MindsetCross-Functional Collaboration

Required

Degree in the field of Computer Science, Data Science, or equivalent technical discipline and/or combined with applied related practical work experience.

Minimum 3 years or more of direct working experience

Expertise in LLM including model architecture, training/finetuning techniques, retrieval augmented generation (RAG, Visual RAG), Generative Feedback Loops (GFLs), Vision Language Models (VLMs), and the value of grounding models with metadata

Experience in knowledge augmented / grounded model LLM technologies (e.g., knowledge graphs, language prompt, neuro-symbolic learning)

Experience in Agentic Al / Agentic GFLs

Experience in multimodal Al technologies / applications

Experience in conversational Al technologies: natural language processing (NLP - e.g., language models, semantic parsing, natural language generation etc.), dialogue (e.g., state tracking, policy learning), and representation learning (embedding, conceptualization, etc.) and knowledge of strengths & weaknesses for automated contextual text extraction

Proficiency in a neural network library (e.g., PyTorch, TensorFlow).

Strong knowledge of vector & vector-enhanced graph DB solutions (e.g. - Weaviate, Chroma, Neo4j, etc.)

Experience in multiple database technologies such as distributed processing (Spark, Hadoop, EMR), MPP (e.g. - AWS Redshift, Presto, Athena, Teradata), NoSQL (MongoDB, DynamoDB, Cassandra)

Experience with Knowledge Representation and Semantic Technologies (OWL, RDF, SWRL, SPARQL, JSON-LD) including semantic modelling, data integration, and data unification

Experience w/ Machine Learning (ML) applied to the scalable automation of data labeling / data tagging of large datasets with technical forensic and/or descriptive metadata

Experience developing and implementing GraphQL APIs and REST APIs

Capable of articulating, verbally and in writing, abstract concepts as well as detailed technical information.

Excellent interpersonal, leadership, and communication skills and the ability to work both independently and with a team.

Comfortable with Agile / Scrum development methodologies

Experience with and/or working knowledge of Jira and Confluence

Preferred

Proficiency with hands on experience working on Python PySpark, familiarity with Java, JavaScript, and/or Scala

Hands-on experience with Graph Query languages (Gremlin, CQL, Cypher, Apache TinkerPop, etc.)

Experience (and/or familiarity) with data visualization tools such as Tableau, Splunk, etc.

Experience with data / KPI dashboards, and report export tools

Basic to advanced familiarity with cloud-based Identity Management Systems such as Okta, Active Directory, OAuth, etc.

Familiarity with zero trust security models

Experienced AWS Cloud Practitioner

Entrepreneurial Spirit: Self-driven and adaptable, with the ability to work in a fast-paced startup environment. Comfortable solving complex problems with minimal guidance.

Growth Strategy Expertise: Proven track record of value creation strategies through data-driven decisions and experimentation. Willing and interested in growing with the company

Customer-Centric Mindset: Experience conducting user research, analyzing customer behavior, and creating strategies based on user needs.

Data-Driven Scaling: Use of data analytics to measure performance. Implement A/B testing and continuous iteration based on insights to optimize growth.

Cross-Functional Collaboration: Work closely with product, engineering, and leadership teams to ensure that growth initiatives align with product development and that new features are based on user feedback and market demand.

Confident in producing and presenting work

Solid understanding of workflows and supply-chains of media, sports, cultural industries

Five to ten + years’ experience in a software development role, information technology role, or related field; five years in management or leadership role

Benefits

Flexible hours and remote work option

Professional development: Access to relevant resources like courses, networking opportunities, public speaking opportunities at industry events & conferences.

Milestone bonuses: Potential for performance-based bonuses or additional equity grants once the company achieves key milestones (such as securing funding or reaching key growth targets).