IBMML

Fast Track Your Data
Discussing competitive advantages created with machine learning, data governance and data science.

What are you most excited to learn more about?

started 6 days ago
#ibmmlFast Track Your Data-Live Q&ALive Q&A with subject matter experts - Machine Learning, getting ready for GDPR, data science...
IBM Analytics1
Thanks to all who joined! Remember: Don’t miss out on Thursday’s #IBMML livestream from Munich, Germany. Register here: ibm.co/2r1CckP.
Fast Track Your Data – Live from Munich - 22 June 2017 - IBM Analytics
Fast Track Your Data – Live from Munich! Be one of the first to see exciting new products, product evolutions, and partnerships, creating a brand new world of enterprise data, built on four essential elements infused with machine learning.
1 Votes Vote
Christopher Penn Thanks for having us! See you all on Thursday's event.
0 Votes Vote
IBM Analytics74
Q2: What should companies offer to attract and retain data scientists?
2 Votes Vote
Dez Blanchfield Free food and beverages ( kidding )
2 Votes Vote
Dez Blanchfield Firstly they should dispel the Unicorn myth / meme and focus on SME skills they need
2 Votes Vote
Christopher Penn A2: Attracting data scientists is partly compensation and partly interesting problems to solve.
3 Votes Vote
Dez Blanchfield Ideally look inside their own teams for SME’s they can train in Data Science
3 Votes Vote
Christopher Penn A2: The best data scientists are practically Holmes-like in rejecting boring problems.
2 Votes Vote
Dez Blanchfield It’s faster to train an in-house SME in Data Science than a Data Scientist a market vertical
2 Votes Vote
Christopher Penn A2: Data scientists are mostly people too. They want to do meaningful work and create impact.
3 Votes Vote
Joe Caserta #datascientist love to solve unique business challenging. Let them do what they love – and pay them well! #deeplearning @IBMAnalytics
3 Votes Vote
Bob E. Hayes Give them the tools that facilitate analytics. Offer them projects with specific goals. Give them clean data. Data scientists are people, too!
4 Votes Vote
Joe Caserta Different jobs require different tools: let your #datascience team use their tools of choice to get their job done. #innovation @IBMAnalytics
1 Votes Vote
jameskobielus The best data scientists will come to you and stay if you give them exciting, challenging, perhaps world-changing projects.
4 Votes Vote
Christopher Penn A2: Also avoid diluting the term data scientist - be sure you're hiring for the real thing and not an analyst.
2 Votes Vote
Joe Caserta #datascience needs a proper laboratory to conduct experiments. Follow corporate data pyramid #cdp architecture@ibmml
3 Votes Vote
Ronald van Loon a data-driven culture and agile multi-disciplinary teams
1 Votes Vote
Dave Vellante put forth a compelling data vision and communicate the link between data and value
2 Votes Vote
Joe Caserta The field of #datascience is growing so quickly, companies must incentivize #datascientist with creative retention packages @IBMAnalytics
2 Votes Vote
jameskobielus You can grow great data scientists internally if you give analytics professionals the opportunity to evolve their skills toward AI/ML/DL etc and apply it all to cool projects that make a difference.
1 Votes Vote
Joe Caserta #datascience needs ephemeral workbenches. Enable fast creation of laboratories on the #cloud with #spark @IBMAnalytics
1 Votes Vote
Ronald van Loon And have the right systems & processes in place, and provide the right tools to foster a culture of data #IBMML
1 Votes Vote
Dez Blanchfield @cspenn free tee shirts don't cut it right ;-)
1 Votes Vote
Dez Blanchfield @bobehayes do you think it is going to shift now that DS is being built into the DNA of the new wave of apps and platforms?
1 Votes Vote
Joe Caserta Beer on tap 24/7 usually helps productivity @IBMAnalytics
2 Votes Vote
Aylee Nielsen I think you need to give data scientists freedom to invent and explore all parts of the business
1 Votes Vote
jameskobielus If you want to seriously recruit groundbreaking data scientists, your team needs to network extensively in their communities, focused on open-source tools (e.g, Spark, TensorFlow, Hadoop, etc.)
1 Votes Vote
Dez Blanchfield @Ronald_vanLoon where do you think folk need to start to make this happen?
0 Votes Vote
Bob E. Hayes Make sure you know what kind of data scientist they are. There are a few different kinds. Hire the right type of data scientist for the right role.
1 Votes Vote
Craig Brown, PhD What I see typically missing is a real plan. Offer #DataScientist a good long term goal. Great tools. Let them know that they will be an important part of the team. They are not just developers that are #SME's
2 Votes Vote
Joe Caserta @bobehayes Exactly!
0 Votes Vote
Dez Blanchfield @Ronald_vanLoon can this be outsourced do you think? i.e. outside SME's teaching the old dog new tricks?
0 Votes Vote
Christopher Penn @dez_blanchfield It's all about aptitude. The dog has to want to learn.
0 Votes Vote
Dez Blanchfield @AyleeNielsen oh god yes, but how do you change long held institutionalised thinking to make this happen ;-(
0 Votes Vote
Bob E. Hayes @AyleeNielsen Totally... While I strive to solve specific problems, sometimes, exploration of other topics, examined in different ways is key to learning new stuff.
1 Votes Vote
Tripp Braden They could develop more comprehensive compensations plans that includes bonuses that are tied to project successes
0 Votes Vote
Joe Caserta @jameskobielus keeping #datascicentist excited... that's the challenge! businesses must evolve to become #analytics-driven
2 Votes Vote
Christopher Penn @TrippBraden Dangerous territory if you're in business units! "Here's what you do should do." "Great, we'll ignore that."
0 Votes Vote
jameskobielus BTW, I should mention money. High-quality proven data scientists are in short supply. They crave challenges, but they're not doing it for charity. Pay them well. But tie their ongoing compensation adjustments to their ability to deliver
1 Votes Vote
Craig Brown, PhD There is no consistency on value. The salary raneg for a sr #DataScientist is too wide.
0 Votes Vote
Dez Blanchfield @craigbrownphd how long do you think folk need to play out, i.e. 90 day plan, 180 day plan, where's the best balance?
0 Votes Vote
Tripp Braden The other challenges I see is that most organizations don't fund continuing education to the level that data team members need to keep growing their skills faster
2 Votes Vote
Dez Blanchfield @craigbrownphd do you think most DS SME's come for the money or the value of the role or compay?
1 Votes Vote
jameskobielus Keeping data scientists in your team will be tough in a market where they have beaucoups opportunities and they're networking like crazy. Give them brag-worthy stuff to do that will help them grow their status while staying on your team.
3 Votes Vote
Craig Brown, PhD Retention is easy. Tools. USing tools like #IBMDSX is a good way to retain good #DataScience resources.
1 Votes Vote
Bob E. Hayes @dez_blanchfield They come for the money. They stay for the fun.
1 Votes Vote
Tripp Braden Most HR leaders try to put formulas around pay paths that do not represent where the market is or should be going to remain competitive
1 Votes Vote
Aylee Nielsen Cross-training data scientists, giving them opportunities to truly develop as thought-leaders and to adopt a broader business mindset - all also very important (but that's true for almost any field)
1 Votes Vote
Bob E. Hayes @jameskobielus Agree... They like to show their work. Let them share their awesome insights.
1 Votes Vote
Aylee Nielsen @bobehayes Story of your life lol
0 Votes Vote
Tripp Braden Many organizations are unsure how to treat Data science professionals and many times lack the capability to build a strong team around key leaders
2 Votes Vote
Bob E. Hayes Also, let #datascientists work as a team of diverse data pros. Not one data scientist knows everything. Having a team helps you build up your ds capabilities.
2 Votes Vote
Bob E. Hayes I did a twitter poll... and here is what I found: https://twitter.com/...
2 Votes Vote
Bob E. Hayes almost half were data scientists; a quarter were data engineers.
0 Votes Vote
Dion Hinchcliffe Publicize your data science investments and efforts. If you're building new data divisions or centers of excellence, let the #datascience community know.
0 Votes Vote