Wunderman Thompson Data, as part of the Wunderman Thompson network, are global data experts redefining what personal​ means for ambitious brands. With a team of 1000+ data scientists, strategists and marketing technologists globally, we deeply understand human behavior to empathize, remember, anticipate and connect with customers to inspire growth.

Wunderman Thompson is a network of over 20,000 people in 90 markets around the world and is uniquely positioned to rethink business, culture and brand experiences, owning delivery from end-to-end. Wunderman Thompson is a WPP company (NASDAQ: WPPGY).

Who we are looking for:

A smart, inquisitive, self-driven Data Scientist to join our growing data science capability within Wunderman Thompson Data Products. You’ll be part of the Data Science Innovation & Engineering group responsible for building scalable data science solutions that can be used across all of our data business.

As a Data Scientist you will be responsible for contributing to the development of machine learning solutions across all our data assets within Wunderman Thompson Data Products. The approach we take within this department is learn fast, innovate well, requiring you to write efficient code, explore approaches and evaluate techniques against performance. You will have the freedom to contribute to methodology decisions and the responsibility of turning your code into production level solutions that can be rolled out across the business.

We’re looking for someone who is genuinely excited about the field of data science right now, driven by continuous learning, development and contributions to the wider community.

What you’ll do:

• Create | Understanding the business problem at hand and where value can come from in terms of Machine Learning and data science. Data wrangling, feature engineering, proper treatment of variable types etc. Methodology selection and testing. Coding solutions to a production level
• Collaborate | Contribute to the wider DSML (Data Science and Machine Learning) community across Wunderman Thompson

Who you are:

• Curious | With an inquisitive mindset you embrace the unknown and see as an opportunity to explore and innovate.
• Ambitious | Willing to take calculated risks, stretch yourself and your team to do new things vs. plugging into existing solutions.
• Passionate | You take great pride in your work. You approach our own and our clients’ business challenges with enthusiasm and a commitment to getting it right. You love working in health. You see data science as a way of expressing creativity.
• Humble | Wear any hat that needs to be worn, and you know you do not know everything. You want to learn from others. 

What you’ll need:

Requirements

• Bachelor’s degree in Machine Learning, Mathematics, Statistics or Computer Science
• Three to six years’ experience
• Strong Applied Machine Learning Experience Including but not limited to:
• Regression (Logistic/Linear/GLMs/Ridge/Lasso)
• Tree Based (XGBoost, LightGBM, RF)
• Clustering (Kmeans/RFM/Hierarchical/HDBSCAN)
• Some Deep learning experience
• Neural networks (MLPs, AEs, CNNs, RNNs LSTMs, GANs)
• Experience in at least one Deep learning framework: Tensorflow, Pytorch, Keras, MXNet, Gluon
• Strong Python, SQL
• Version Control – Git
• Strong examples of independently developed machine learning pipelines end-to-end, from problem formulation, data pre-processing, feature engineering, model optimization, and deploying models into production

Preferred Qualifications

• Master’s degree in Machine Learning, Mathematics, Statistics or Computer Science
• Strong NLP Experience:
• Word2Vec, GloVe, LTSMs, LDA, NER, Probabilistic Language Models  
• Apache Spark
• IBM Watson Cloud Pack or other cloud machine learning platform
• Using GPUs/TPUs for accelerating algorithms
• Apache Spark (Pyspark, Sparklyr or Scala) for scaling algorithms
• Cloud services experience to implement and scale algorithms
• Ability to explain model output and ML approaches to non-technical audiences
• Ability to interpret and communicate insights, build story & visualization from ML model outputs
• An eagerness to develop exciting data science solutions that will have a tangible impact on the business
• Hard working and focused
• Strong collaboration and communication skills
• Self-sufficient