Data Science and Algorithms Lead
Talkdesk, Inc
há 2 dias

Together at Talkdesk, we’re building a future of brilliant customer interactions. We have the cleverness, curiosity, and grit to make us a team of customer heroes : thinkers, achievers, and dreamers who believe that our world-

class SaaS platform can influence a new kind of customer interaction.

Talkdesk started from a hackathon win and within five years has become one of the fastest growing companies in the world, identified as a Visionary by Gartner, and enabled 100,000,000+ customer interactions using our platform.

With $124.5 million in backing from DFJ, Salesforce Ventures, Storm Ventures, and Viking Global Investors and supported by the successes of our 1,400+ customers from Peloton, IBM, Wounded Warriors Project, and MongoDB, Talkdesk is disrupting a $40+ billion stagnant market.

We’re now looking for the new members of the Talkdesk family - those ambitious, driven, and collaborative individuals who thrive in a fast-

paced environment and will push us to do even greater things together. If you would like to help us shape the future of Talkdesk, come along with us on our journey -

your dream job is waiting!

Responsibilities :

  • Create computer simulations to support operational decision-making.
  • Math modeling and NP / combinatorial heuristic search including local search, branch and bound, and simulated annealing.
  • Probability and statistics, exploratory data analysis, linear regression, hypothesis testing.
  • Able to convey mathematical results and algorithms in plain English.
  • Functional thought leader, sought after for key tech decisions.
  • Requirements :

  • MSc or PhD in Computer Science, Mathematics or Statistics;
  • At least 2 years in a technical management or technical lead role
  • Experience working in an agile software environment.
  • Experience with unit testing and integration testing.
  • Experience with patents applications and research papers.
  • Experience programming production code in C#, C++, or Python.
  • Experience with SQL or NoSQL queries.
  • Experience and insight into statistical and machine learning models such as regressions, Markov, decision trees, clustering, neural networks, convolutional networks, deep learning, graphs, LDA, SVM.
  • Experience with time series analysis.
  • Experience with machine learning tools, open source packages, or services (e.g. Mallet, Tensor Flow, SageMaker).
  • Nice to Haves :

  • Experience with Big Data ML toolkits, such as Mahout, SparkML or H20, Hadoop, Spark, Flink, Kafka
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