Managing Data Science Teams @ DataNights

Cohort 3, in preparation

Managing Data Science Teams @ DataNights

DataNightsInstructor

The third DataNights Data Science Management cohort is currently being assembled, with a refreshed session pool that leans more heavily into AI-era management, LLMOps, hiring in a changing landscape, and organizational influence.

Cohort 3 is currently in preparation. Dates, final venue, and the hosting company will be added here once the cohort is finalized.

Organizing Team

  • Shay Palachy Affek - Program lead, DataNights / Datahack
  • DataNights / Datahack organizing team - Cohort planning, speaker coordination, and operations

Current Session Pool

The speaker lineup and final syllabus are still being finalized. The items below reflect the current session pool driving the next cohort.

  • Make It Worth It - Inbal Budowski-Tal (returning candidate) A returning opening lecture about what it means for data science to matter in production and in the business.

  • LLMOps for DS Managers - TBD (candidate) What a data science manager needs to understand about modern LLM pipelines, evaluation, latency, and cost.

  • Code Assistance & the New Code Review - TBD (candidate) Managing code quality, ownership, and standards when AI tools write the first draft.

  • Build, Buy, or Fine-Tune? - TBD (candidate) A practical framework for choosing between building from scratch, buying, fine-tuning, or using RAG.

  • The MVP Mindset - Topaz Gilad (returning candidate) A returning session on iterative product thinking and defining success before building.

  • The False Promise of Easy POCs - Mica Rubinson (candidate) Why AI prototypes are easy to demo but much harder to turn into systems that actually deliver.

  • The Interview Framework - Shay Palachy Affek (returning candidate) A structured approach to hiring and evaluating data scientists across different interview formats.

  • DREAM - Team Archetypes - Nurit Vatnik (returning candidate) Using archetypes and team composition ideas to decide what kind of people a data science group actually needs.

  • Managing Juniors - Alice Fridberg (returning candidate) How to build better onboarding, autonomy, and feedback loops for junior data scientists.

  • The Secret Sauce - Shir Meir-Lador (returning candidate) A candid look at what distinguishes great data science managers from merely competent ones.

  • Building the Coalition - Shay Palachy Affek (returning candidate) Working across a larger organization when you do not directly control the people or priorities you depend on.

  • The DS Project Frameworks - Shay Palachy Affek (returning candidate) A practical framework for scoping, running, and closing ambiguous data science initiatives.

Course Outline

The final syllabus is still being assembled for cohort 3. This page will link to it as soon as it is ready.