About Black Swan Data

We are a Data Science & Creative Technology Company. We help our clients find insights and solutions that change the way they think about their business. We analyse consumer behaviour, then build cutting edge technology to create better outcomes for our clients. 

Our name is derived from an ancient assumption that all swans were white, until a European explorer travelling to Australia in 1697 saw some black swans and had what is known as a ‘black swan moment’.  2 years after launch, we’re already 120 people and now have offices in Waterloo, Exeter, New York, Hungary, California and Cape Town.

A great opportunity to join a rapidly growing data and technology agency led by an experienced management team. Being passionate, a team player, and a go-getter are essential to working for this up and coming agency based in central London.      

Black Swan has been awarded the top position in the Sunday Times Sage Start-Up Track 15 list. 

Summary:

Your mission at Black Swan will be to support development of the data science capability which underpins our core product(s). As a Senior Product Data Scientist you will be responsible for working with stakeholders both inside and outside of the business to define, explore and prototype new product features or improvements to existing product features.

This will involve working closely with internal insights teams or with clients to create new and innovative solutions to business problems. Secondary priorities will involve supporting consulting projects.

Your duties as a Senior Product Data Scientist would include:

  • Working with time series and social data to provide creative data science solutions for our core product line. 
  • Both iterative improvements to existing capability and new feature development.
  • Working with non-technical teams across the company to understand requirements and deploy prototype solutions.
  • Supporting consulting projects on occasion.

Personal Attributes

  • Proven ability to translate business and user needs into data science requirements.
  • Highly creative.
  • Organised, and comfortable in an agile work environment.
  • Team player, willing to support others and engage with other teams across the business.
  • Excellent people skills and great communicator.
  • Strong written communication and ability to clearly document work.

General Requirements

  • Master’s degree in Computer Science, Mathematics, Physics, Engineering or other physical science.
  • Proven track record of applying machine learning techniques in a commercial context.
  • Experience working with social data (i.e. Twitter, Tumblr, Reddit, news articles, blogs, etc).
  • Deep understanding of core machine learning concepts.

Specific Requirements

  • Proficient programmer in Python with solid software development standards, including version control (git), testing (unittest/pytest) and virtual environments.
  • Experienced working with non-technical stakeholders and clients.
  • Experience with time series forecasting and decomposition.
  • Experience with Natural Language Processing (NLP) – e.g. relevancy, topic modelling.
  • Unsupervised machine learning techniques – e.g. clustering, dimensionality reduction.

Desirable skills

  • Experience with Spark/PySpark and working with ‘big data’.
  • Experience or familiarity with consumer research techniques, especially surveys.
  • Programmer in Scala.
  • Knowledge of network science. Comfortable creating and working with graphs and preforming community detection, finding connected components, eigenvector centrality etc
  • Experience with Databricks.
  • Experienced in agile development.
  • Experienced in product-driven data science development.

What makes a Swan? 

We want people fanatical about creating innovative solutions inspired by data. We know Black Swan’s DNA is different, it’s what helps us find new perspectives on our clients’ problems. Working in a fast paced, energised environment, our bar is set high, and an ability to build long lasting partnerships both internally and externally is vital.

We have made a difference at our core and that is embedded in our values.

  • We believe in long-term partnerships through transparency and honesty
  • We believe in leaving the world in a better place than we found it
  • We believe anyone can achieve great things. We do not put people in boxes
  • We listen more than we talk
  • We think 10% crazy is just about right!
  • Most importantly, and because you spend 60% of your waking time at work, we believe you should enjoy it

What We Offer?

Remote Working - Until it is safe to return to our offices, and then up to 60% of your working month working remotely when we are back in our Hubs. Some roles will also be eligible to apply for 100% remote working.

Exciting Clients and Projects - Working with Black Swan we promise to provide an exciting and ever-changing industry within Data Science and Predictive Analytics, with challenging projects serving some of the leading Brands in each domain

Talented Teams -  We hire highly skilled and multi-disciplined teams over the world. We have 8 offices across 4 countries!

Career Development - Regardless of which area of the business you work in you can expect to collaborate on all aspects of Black Swan’s projects gaining the exposure you need to develop your expertise. No matter what stage you are in your career your development is our priority.

Working environment - Because you spend 60% of your time at work, we try to make it enjoyable! You will benefit from our global benefits: Share options, staff referral scheme, duvet day, flexible and remote working, internal and online training initiatives, volunteering opportunities at white swan, birthday lie in, Christmas gift cards, quarterly staff events, summer hours and Flexible Leave Policy.

As well as the benefits unique to our Cape Town office - Pension & Risk benefits, medical aid contribution, enhanced maternity & paternity leave, parking, breakfast, drinks & snacks, fun Fridays, yoga and meditation sessions.

We want to positively change the future through technology and the power of prediction. How about you?

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