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CLIENT-FACING DATA SCIENCE

CLIENT-FACING DATA SCIENCE. TAKA TANAKA. WHO IS SCHIRESON?. Schireson is a consulting company providing marketing strategy, data science, and software solutions to clients in a wide range of industries. SCHIRESON HAS 115 EMPLOYEES AS OF JANUARY 2019. MEMBERS BY DEPARTMENT. Operations.

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CLIENT-FACING DATA SCIENCE

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  1. CLIENT-FACINGDATA SCIENCE • TAKA TANAKA

  2. WHO IS SCHIRESON?

  3. Schireson is a consulting company providing marketing strategy, data science, and software solutions to clients in a wide range of industries.

  4. SCHIRESON HAS 115 EMPLOYEES AS OF JANUARY 2019 MEMBERS BY DEPARTMENT Operations Data Science Strategy & Consulting Engineering & Product Analytics

  5. OUR DATA SCIENCE DEPARTMENT HAS 36 MEMBERS HIGHEST DEGREE Ph.D. Bachelor’s Master’s SUBJECTS OF HIGHEST DEGREE Economics History Biology The Schireson team has 115 members, including 31 in Engineering & Product, 15 in Analytics, 13 in Strategy & Consulting, and 20 in Operations. Chemistry / Mat. Sci. Physics / Astronomy Political Science Computer Engineering Business Mathematics

  6. PROJECT EXAMPLES

  7. Advanced Advertising (Major media companies) “How can we advertise to the most relevant audience for each product (instead of the traditional gender-age demographics)?” • We use statistical matching to identify custom audience segments (e.g. “Fast food lovers,” “Likely car buyers”).This creates targeting advantages for the advertisers, and arbitrage opportunities for the publishers. • We train a predictive algorithm to identify when audience segments are most likely to tune in. • We use the predictions and work with clients to optimize ad placement. ?

  8. Intelligent Marketing (Major tech company) • Survey thousands of representative consumers who will buy a device in the future, and determine the baseline average likelihood to buy specific products. • Build machine learning models to determine what demographic and attitudinal factors are most predictive of making a purchase. • Identify the best micro-segments and map them in terms of targetability and marketing cost. • Fine-tune and optimize the message for each segment. “How should we market a new tech device? Whom should we target, and how?” ?

  9. Data Management Consulting (Major media company) • Conduct dozens of interviews of stakeholders (senior executives, marketing analysts, data analysts, software engineers) to understand current work flow and identify where they most want to see change. • Scrutinize production databases and code to identify broad and specific areas for improvement. • Deliver a comprehensive set of actionable recommendations, including detailed execution plans for staffing, timelines, and organizational shifts. “How do we manage data efficiently at scale, and build a world-class data analytics team?”

  10. What makes“client-facing” data science different?

  11. WHAT IS IT LIKE TO BE A DATA SCIENCE CONSULTANT? • We get to be the secret weapon. • Our clients trust and value our work. They come to us with their toughest problems. • … but our work takes place in the shadows. Our work is in the news, but our name is almost never printed. • It’s fast-paced. • We make promises. We deliver. We exceed expectations. • While we do have some internal R&D projects, most of our work is catering to what our clients need this month. • There’s always something new going on. • We lead with innovative applications of DS in business. • Every client has their own needs and preferences. • We get to work alongside brilliant, collaborative teammates. • We don’t hire PhDs. We hire people who think scientifically, take pride in doing great work, and care about their peers.

  12. THE CLIENTS ARE THE EXPERTS • LISTEN AND LEARN • The balance to strike: “We know what we’re doing, and we will also ask many questions.” • Draw on their expertise to learn what they need. • How did they get here? What’s good? What’s hard? • What other solutions have they considered? • What is the most important? What does success look like? • Have they evaluated how a solution here might work with future/parallel initiatives? • They know better than anyone about their KPIs, and how to interpret them. • But they are usually not familiar with machine learning or clustering approaches. • Each client is different, even when some come to us with similar requests.

  13. WE ARE THEIR CONSULTANTS, NOT THEIR EMPLOYEES • THE WORK DYNAMIC IS FUNDAMENTALLY DIFFERENT • How do you decide when the work is done? • How will success be measured? • If we build a machine learning model, who owns the IP?Who maintains it down the road? • Having a working line of communication and collaboration is key.e.g. email, regular meetings, Slack, phone • Our points of contact will be the gatekeepers to other stakeholders.

  14. IT’S NOT OUR DATA • ESTABLISHING ACCESS IS ABOUT TRUST. IT TAKES TIME AND WORK. • Does our point of contact have direct ownership of the data? • Build a working relationship with the people who do. • How will we work with the data? • Credentials to their warehouse • Locked computers or VPN access • Data delivery (e.g. SFTP, physical delivery) • Workplace immersion; Slack • We work with different companies in the same industry. • This comes with ethical and legal responsibilities. • Sometimes, it is necessary to assure clients that we do not mix data (even internally) from different businesses. • Story: Once upon a time, a media data company…

  15. COMMUNICATION (TECHNICAL) • “ANY SUFFICIENTLY ADVANCED PIECE OF TECHNOLOGY IS INDISTINGUISHABLE FROM MAGIC” • The mystique of machine learning is a double-edged sword.Like all forms of magic, there will be a mix of awe and skepticism. • Explaining model features can help build comfort and trust. • Know which stakeholders to have detailed technical discussions with. • Interpretability of results is often important. • This may be a reason to opt for simpler models, if the situation allows. • … or have interpretation engines like LIME ready. • The evidence is our friend. (We are scientists, after all!) • Set sensible benchmarks using KPIs they embrace. • Be prepared to measure and evaluate the results.

  16. COMMUNICATION (RELATIONSHIP MANAGEMENT) • AGAIN, IT COMES DOWN TO TRUST. OUR SUCCESS MUST BE THE CLIENTS’. • We help. We do not sell. • Our work has to be right for this client. • And our value is measured by… well, the data. • Be ready for them to ask for more. • Many client relationships begin with a pilot project. • Some pilot projects have natural follow-ups or expansions;other follow-ups can be very different. • Understand that stakeholders have different needs. • C-suite executives are often delighted by simple success stories (e.g. one number, one plot). • Others often want attention to detail and availability. • Reputation is vital. • Clients have their own networks, and stakeholders can switch roles or jobs.

  17. SUMMARY Schireson works with a diverse set of clients, who entrust us with their data and workflows driving billions of dollars of revenue. Because each client is different, every project brings something new. Below are some principles I have found to be consistently fruitful: • Learn from the client. They know the most about their business. • Understand what is important to each stakeholder, from execs to analysts. • Collaborate in real-time if possible (e.g. office immersion, Slack). • Set clear expectations. • What defines success? What are the deliverables? What access do we need? • … and be happy to exceed them! • Strive to build institutional trust with excellent work and candor. • Communicate machine learning and advanced analytics approaches. • Prove the value of the work; establish sensible benchmarks using their KPIs.

  18. Thank you! taka@schireson.comLook for us at the Career Fair tomorrow!

  19. HOW I GOT HERE • (IT’S OKAY TO NOT KNOW, AND TO EXPLORE!) while teachinghigh school part-time Exited w/ Master’s Finance Undergrad PhD (2011) Learned Python &machine learning(2017) Postdoc #2 Data Scientist Postdoc in Munich

  20. SCHIRESON IS A LEADING DATA SCIENCE FIRM DELIVERING TRANSFORMATIVE SOLUTIONSIN MARKETING AND MEDIA STRATEGY SCIENCE SOLUTIONS Insights into consumers, brands, and market opportunities that support bold strategies and business growth for our clients. World-class data science and advanced mathematics that empower our clients to understand what’s working, what’s not, and how to use marketing and media to win. We build proprietary software that connects our insights and science to the business engines that deliver the results our clients depend on.

  21. WE’VE BEEN HELPING A BROAD RANGE OF CLIENTS NAVIGATE UNCERTAINTY AND ACCELERATE GROWTH FOR OVER 15 YEARS

  22. WE OPERATE GLOBALLY FROM A NETWORKOF OFFICES ACROSS THE U.S.  SEATTLE BOSTON NEW YORK(HQ) SAN FRANCISCO AUSTIN

  23. WE COME FROM DIVERSE BACKGROUNDS AND EXPERIENCES, BUT WE COLLABORATE AS ONE TEAM. TOGETHER, WE ARE COMMITTED TO SIMPLY MAKING THINGS WORK BETTER.

  24. WHAT WAKES US UP IN THE MORNING? OUR DRIVE TO SOLVE TOUGH, IMPORTANT PROBLEMS FOR OUR CLIENTS. OH, AND COFFEE.REALLY GOOD COFFEE.

  25. GET TO KNOW US 227,000 Consumers surveyed in past 12 months 76 Vacation bonuses given in past 12 months

  26. GET TOKNOW US 3,250 Cups of coffee served per month 4.7 Office playlist debates per day 700 Crossword puzzle clues solved per week

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