Recognized for its innovative impact, Udacity part of Accenture continues to empower people with the skills they need to secure the jobs they want.

Our School of Data is committed to providing high-quality upskilling opportunities in this rapidly evolving field. We regularly launch new projects and are seeking experienced mentors to join us as external contractors to support our programs and learners.

As new initiatives arise, we will reach out to qualified candidates within this talent pool to provide details on project scope, expected timelines, and compensation. If you are passionate about tackling meaningful challenges and making a difference we invite you to apply and explore this opportunity to collaborate with us. 

You’ll be an excellent fit if you have:

• Proven technical expertise with 5+ years of experience in the relevant field
• A passion for mentoring and helping others succeed in their learning
• Excellent interpersonal skills. You enjoy building relationships, communicating effectively, and fostering a positive learning environment 
• A deep understanding of the tech industry and emerging trends in AI and related fields
• The flexibility to work part-time as an external contractor alongside your current commitments

Mandatory Technical Skills – School of Data

• Proficiency in Python and/or SQL
• Strong understanding of data analysis, statistics, and data modeling concepts
• Experience with data manipulation and visualization tools (Pandas, NumPy, Excel, Tableau/Power BI)
• Familiarity with ETL processes and data pipelines
• Understanding of databases (relational and/or NoSQL)
• Knowledge of data warehousing concepts and architecture
• Ability to work with large datasets and optimize data workflows
• Experience with data quality, validation, and governance practices
• Strong problem-solving and analytical skills

Preferred:

• Experience with big data tools (Spark, Hadoop)
• Familiarity with cloud platforms (AWS, GCP, Azure)

Exposure to real-world data projects (analytics, engineering, or architecture)

Responsibilities:

Your responsibilities as a technical mentor will be divided into three major tasks.

1. 1:1 video calls
2. Virtual Technical Deep-Dive Sessions
3. Group Q&A sessions

Personal 1:1 Session:

• Provide personalized support by addressing learner questions related to course content and projects.
• Prior to the call mentors are expected to review the students' previous project submission(s) - provided by the Mentor Success Team when available - and/or any specific areas of the Nanodegree content or project that the student has expressed confusion or difficulty with.

Technical Deep-Dive Session:

• For concept deep-dives, mentors will come prepared with a slide presentation that reviews a Nanodegree concept in more detail, share different use-cases for the concept to broaden student perspectives and understanding, and hold a Q&A session with the learners.
• For project walkthroughs, a mentor will come prepared with a slide presentation that outlines each element of the rubric to help learners understand expectations and typical problem areas they may encounter. This can include a mentor “grading” a sample submission to demonstrate what mentors are looking for when reviewing projects.

Group Q&A Session:

• Host regular sessions (via Slack or video) to address learner queries related to projects and coursework. No prior preparation required.

Why should you apply? 

• Make an impact by mentoring and contributing to a vibrant, global learning community
• Showcase your expertise and gain recognition for your technical knowledge
• Learn and network with our global community of mentors while staying ahead of the curve on cutting-edge technologies
• Earn additional income with the flexibility to work on your own schedule

Mentoring at Udacity offers a unique opportunity to make a significant impact on the lives of learners and to contribute to achieving our mission. 

If you're passionate about learning, technology and want to make a positive impact, we encourage you to apply to become a mentor at Udacity part of Accenture. 

Let's work together to shape the future of tech education!

We’re seeking a Data & AI Engineer to develop intelligent data pipelines and analytics solutions that power smarter decisions across silicon design, verification, and manufacturing. You’ll transform engineering data into actionable insights through automation, modeling, and visualization.

Responsibilities

• Build and maintain data pipelines to support machine learning and analytics workflows.
• Collect, clean, and transform large, complex datasets from engineering environments.
• Develop and train predictive models for yield, performance, and anomaly detection.
• Automate recurring data analysis tasks and integrate models into engineering processes.
• Collaborate with design and software teams to embed AI-driven insights into products.
• Create dashboards and visualization tools for reporting and decision-making.
• Document code, models, and processes for transparency and reproducibility.

Qualifications

• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Strong skills in data manipulation (Pandas, NumPy, SQL).
• Experience with workflow orchestration (Airflow, Spark, or similar).
• 3–5 years of experience in data engineering or applied AI.
• Bachelor’s degree in Electrical Engineering, Computer Science, or related field.

Preferred / Plus

• Familiarity with semiconductor design, verification, or manufacturing datasets.
• Understanding of statistical modeling and predictive maintenance.
• Experience with cloud environments (AWS, Azure, GCP) and version control (Git).
• Knowledge of MLOps principles (deployment, monitoring, CI/CD).

AI Course Builder – Business & Finance Applications

About Wall Street Prep

Founded in 2004 by investment bankers, Wall Street Prep (WSP) is a leading provider of professional skills training in financial and valuation modeling. Our mission is to bridge the gap between academia and the real world by equipping finance professionals and students with practical, hands-on skills.

We partner with top-tier investment banks, private equity and investment management firms, Fortune 500 companies, and elite undergraduate and MBA programs. Our training is delivered through engaging in-person classroom sessions and via our industry-leading online learning platform, all designed by experienced finance professionals.

As artificial intelligence rapidly transforms financial services, WSP is expanding its AI curriculum to help finance professionals integrate modern AI tools directly into their workflows.

Position Overview

Wall Street Prep is seeking AI Course Builders with strong practical experience using modern AI tools and automation workflows to help develop short, practical AI courses for finance professionals.

In this role, you will focus on designing hands-on AI learning content rather than delivering live instruction.

You will work with WSP’s learning team to develop high-impact modules that teach finance professionals how to apply AI tools to real business tasks, such as research, financial analysis, workflow automation, and productivity.

This includes building course content centered around leading AI assistants and enterprise AI platforms such as ChatGPT, Claude, Gemini, Microsoft Copilot, Perplexity, Rogo, and Shortcut, along with Python-based workflows and API integrations.

Your work will directly shape how professionals in investment banking, private equity, asset management, consulting, and corporate finance adopt AI in their day-to-day work.

Key Responsibilities

AI Course Development

Design and build practical learning modules covering topics such as:

• Foundations of generative AI and large language models
  
  
• Prompt engineering for business workflows
  
  
• AI-assisted research and knowledge synthesis
  
  
• AI-assisted financial analysis and modeling
  
  
• Workflow automation using AI tools
  
  
• AI productivity tools for analysts and professionals

Hands-On Exercise Design

Develop real-world exercises and labs that teach professionals how to use AI tools in practice, including:

• Using ChatGPT, Claude, Gemini, and Perplexity for research, analysis, and writing
  
  
• Leveraging Microsoft Copilot, Rogo, and Shortcut to automate workflows and productivity tasks
  
  
• Building prompt workflows for financial analysis and research
  
  
• Creating simple Python-based automation scripts
  
  
• Demonstrating AI-assisted coding and data analysis

Practical Use Case Development

Create applied case studies that demonstrate AI in real-world business and finance contexts, such as:

• Investment research and summarization
  
  
• Financial data analysis and visualization
  
  
• Competitive analysis
  
  
• Document review and synthesis
  
  
• Workflow automation and productivity tools

Collaboration with the Learning Team

Work with WSP’s instructors and learning designers to:

• Translate technical AI concepts into practical business workflows
  
  
• Develop structured course modules and exercises
  
  
• Update content as AI tools rapidly evolve
  
  
• Ensure courses are practical, relevant, and accessible to finance professionals

What We Are Looking For

Experience

3+ years of experience working with AI tools, machine learning, data science, or AI-enabled workflows.

Strong practical experience using modern AI assistants and enterprise AI tools such as:

• ChatGPT
  
  
• Claude
  
  
• Gemini
  
  
• Microsoft Copilot
  
  
• Perplexity
  
  
• Rogo
  
  
• Shortcut
  

Experience applying AI tools to real-world workflows such as research, analysis, automation, coding, or productivity.

Experience building technical content such as:

• technical tutorials
  
  
• course materials
  
  
• developer documentation
  
  
• technical blog posts
  
  
• learning modules or workshops

Experience in finance, consulting, or corporate environments is a plus but not required.

Technical Skills

Practical expertise using generative AI tools including:

• ChatGPT
  
  
• Claude
  
  
• Gemini
  
  
• Perplexity

Experience with AI productivity tools and workflow assistants such as:

• Microsoft Copilot
  
  
• Rogo
  
  
• Shortcut

Python programming experience strongly preferred, including libraries such as:

• Pandas
  
  
• NumPy
  
  
• Matplotlib
  
  
• scikit-learn

Experience working with AI APIs and frameworks such as:

• OpenAI API
  
  
• Hugging Face
  
  
• LangChain
  
  
• similar AI tooling

Working Arrangement

This role is project-based or part-time, focused on building course materials for upcoming AI training programs.

The position is remote-friendly.

Content developers will collaborate closely with WSP’s learning team and instructors.

Compensation

Highly competitive project-based compensation depending on experience and scope of work.

Why Join Wall Street Prep

Help shape how AI is taught to professionals across global finance.

Build practical AI learning content used by professionals at leading financial institutions.

Collaborate with a highly experienced team of finance and training experts.

Contribute to one of the fastest-growing areas of professional education.

Join the core team at Eclipse, where we’re building an AI agent-first marketplace that connects intelligence with real-world tasks, starting with data collection and labeling. We are seeking a Data Scientist to establish the foundation for how our data is labeled, processed, and prepared for consumption by next-generation Large Language Models (LLMs). Your work will be critical in transforming our raw data collections into valuable, AI-ready datasets.

Qualifications 

• Proven experience as a Data Scientist or Machine Learning Engineer with a focus on data quality and preparation.
• Strong understanding of data labeling methodologies and hands-on experience with data annotation platforms and workflows.
• Demonstrated experience preparing datasets for training and fine-tuning Large Language Models (LLMs), including knowledge of techniques like tokenization, embeddings, and NER.
• Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn, spaCy, Hugging Face).
• Experience using APIs/SDKs to automate data annotation and active learning loops.
• Excellent communication skills, with an ability to create clear documentation for technical and non-technical audiences.

Responsibilities 

• Develop Data Labeling Strategies: Design and document a formal data annotation strategy, including clear, scalable, and efficient guidelines for labeling our data. Define and enforce quality metrics, including inter-annotator agreement.
• Optimize for LLM Consumption: Research, define, and prototype the optimal data formats, structures, and pre-processing steps required for fine-tuning and training LLMs on our datasets.
• Data Quality Analysis: Establish automated processes and metrics to analyze the quality of both raw and labeled data, providing feedback to improve our data collection and labeling workflows.
• Collaborate with Engineering: Work closely with the engineering team to guide the implementation of data processing pipelines and ensure the data infrastructure meets the needs of ML applications.

Nice-to-Haves

• Experience with audio data processing and relevant libraries.
• Familiarity with data annotation platforms and tools.
• Knowledge of modern MLOps principles and practices.
• Experience with large language model data curation and Reinforcement Learning from Human Feedback (RLHF) pipelines.

Join the Eclipse team!

Eclipse is building the fastest Ethereum Layer 2, powered by the Solana VM. Our general-purpose L2 combines the best of the modular stack without sacrificing UX or fragmenting liquidity. On top of this foundation, we’re building apps in-house and iterating quickly to find breakout consumer and AI experiences. We’re backed by top investors including Polychain, Tribe Capital, Placeholder, and DBA.

• Opportunity. We believe blockchains should be fast AND highly usable. You’ll do high-impact work to enhance Ethereum’s scalability, shaping the future of crypto
• Flexibility. We collaborate synchronously and asynchronously, across weekly all-hands meetings, Slack messaging, and quarterly in-person meetups
• Team. Our founding team has experience launching and scaling blue-chip projects such as dYdX, Uniswap, and zkSync. We’re backed by leading funds and leaders including Polychain, Tribe, Placeholder, DBA, Mustafa Al-Bassam, Tarun Chitra, Meltem Demirors, and others
• Culture. As an early member of our team, you’ll have a unique opportunity to help shape our culture. We value intellectual honesty, bias towards action, and believe every member plays a key role in achieving our ambitious goals
• Compensation. You’ll receive a competitive salary + equity + benefits package.

Eclipse Laboratories is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, veteran status, or any other status protected by applicable laws or regulations. All employment decisions are based on qualifications, merit, and business need.