Data scientists vs. Statisticians: Lessons learned after two years of practical experience
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Data scientists vs. Statisticians:
Lessons learned after two years of
practical experience
Prof. Dr. Bertrand Loison, Swiss Federal Statistical Office, Vice-Director
5th International Conference on Big Data for Official Statistics
Session “Data Science and Capacity Development in Official Statistics”
Kigali, Rwanda, 3 Mai 2019
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 1
Two years of practical experiences (2017 – 2019)
FEUILLE DE ROUTE POUR L’IMPLEMENTATION AU SEIN DE L’OFS DE LA STRATEGIE D’INNOVATION SUR LES DONNEES
01.01.2017 - 01.04.2017 - 01.07.2017 - 01.10.2017 - 01.01.2018 - 01.04.2018 - 01.07.2018 - 01.10.2018 - 01.01.2019 - 01.04.2019 - 01.07.2019 - 01.10.2019 -
31.03.2017 30.06.2017 30.09.2017 31.12.2017 31.03.2018 30.06.2018 30.09.2018 31.12.2018 31.03.2019 30.06.2019 30.09.2019 31.12.2019
Version 1.0 / 31.10.2017 Délivrables
T1 T2 T3 T4 T1 T2 T3 T4 T1 T2 T3 T4
01.01.2017 01.04.2017 01.07.2017 01.10.2017 01.01.2018 01.04.2018 01.07.2018 01.10.2018 01.01.2019 01.04.2019 01.07.2019 01.10.2019 31.12.2019
Meilleures pratiques Rapports de voyages GWG Big
Un Statistical Commission – UN Global Working Group on Big Data for Official Statistics (https:// unstats.un.org/bigdata/)
internationales Data
Cohérence avec le MJP 2020 - 2023
Définition de la Définition de la stratégie 2017-2019 (S1.1) Définition de la stratégie 2020-2023 (S1.3) Stratégie Data Innovation 2020 –
+ =
stratégie (S1) Définition de la feuille de route 2017-2019 (S1.2) Définition de la feuille de route 2020-2023 (S1.4) 2023 (S1.1 – S1.4)
+
Workshop avec les cadres de chaque division métier Aquisition d’expérience pratique. Input pour l’élaboration du MJP 2020 - 2023
Stratégie (S)
Phase pilote de mise Identification des projets Reporting devant la GL et rapport
Projets pilotes (1 par division BB, WI, GS, RU, REG) (S2.2)
en oeuvre (S2) pilotes (S2.1) de fin projet (S2.1 – S2.2)
Evaluation de la Evaluation des projets
Rapport d’évaluation (S3.1)
phase pilote (S3) pilotes (S3.1)
Soutien donné par Statoo Consulting et METH
Soutien «On the job» Plan de soutien Soutien spécifique du personnel faisant partie des projets pilotes Plan de soutien «On the job»
(C1) est prêt (C1.1) (C1.2) (C1.1 – C1.2)
Compétences (C)
Soutien donné par Statoo Consulting et METH Intégration dans la formation officielle EducStat
Formation «Off the Soutien des membres du comité de direction concernant les Concept de formation «Off the
Conception d’un module de formation (C2.2)
job» (C2) approches relatives à la science des données. (C2.1) job» (C2.1 – C2.2)
Evaluation de la Définition de la stratégie 2020-2023 (S1.3)
Rapport d’évaluation (C3.1)
phase pilote (C3) Définition de la feuille de route 2020-2023 (S1.4)
Inventaire des données consolidées présentent ou pas dans la KD
Accès aux données Inventaire de base des sources de Saisie des métadonnées dans Inventaire des sources intenes
internes (DI1) données internes. (DI1.1) SMS (DI1.2) dans SMS (DI1.1 – DI1.2)
Accès aux données Liste des data brokers
Données et infrastructure (DI)
Identification du potentiel des data brokers comme «livreurs/fournisseurs» de données (D2.1)
externes DI2) intéressants pour l’OFS (DI2.1)
Draft des nécessaires
Bases légales (DI3) Identification du potentiel des data brokers comme «livreurs/fournisseurs» de données (D2.1) modifications des bases légales
(DI3.1)
Infrastructure Open Source A intégrer dans la SIP 2020-2023
Plateforme Mise en place de l’infrastructure Besoins métiers Infrastructure pilote + besoin
informatique (DI4) pilot (DI4.1) formulés (DI4.2) métiers pour SIP (DI4.1 – DI4.2)
Evaluation de la Evaluation de l’infrastructure
Rapport d’évaluation (DI5.1)
phase pilote (DI5) pilote (DI5.1)
Communication Reporting, workshops et articles
Communication
interne (CO1) (CO1.1 – CO1.10)
(CO)
Présentation de la stratégie dans la domaine public 1er Datathon OFS 2019 Articles scientifiques
Communication Préparation de la présentation Mobilisation de la communauté Communication concernant les 1er Datathon OFS 2019,
Conception Datathon 2019 (CO2.1)
externe (CO2) lors des JSS 2017 (CO1.1) (CO2.2) projets pilotes (CO3.1) communications (CO2.1 – 2.8)
GL-Antrag GL-Reporting Kick-off interne Communication publique Assemblée des cadres Journal interne Regiostat Fedestat
Sources:
Data Innovation Strategy 1.0 : https://www.bfs.admin.ch/bfs/en/home/news/whats-new.gnpdetail.2017-0673.html
Pilot Projects : https://www.experimental.bfs.admin.ch/en/
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 2
Agenda 1. What did we do ? 2. What are our experiences ? 3. What will be the next major step ? 5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 3
We have created an ad-hoc agile organization inside FSO - #1
Rules
1. Ad-hoc organization is under
the final responsibility of a
board member.
2. Members of the ad-hoc
organization have been stayed
subordinated in their line
organization !
3. Five pilot projects are
managed by the ad-hoc
26 people (Statisticians, Methodologists, IT Specialists) organization. The final goal is
aged between 26 and 58 years old ! to go into production at the end
of 2019.
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 4
1. We have created an ad-hoc agile organization inside FSO - #2
Pilotproject X
Methodolo
Analysts
gists
IT
Specialists
• Classical hierarchy that needed to be forgotten…
• High degree of autonomy was and is still required…
• Choosing the right people at the beginning was not easy…
Source: European Commission, Open Data Maturity in Europe 2016, Figure 32, October 2016 (goo.gl/WPHR54)
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 52. We have complemented their skills with off- and on-the-job teaching - #1
Off-the-job (9 x 1 day = 9 days dispatched over 3 months)
• R for Data Science • Decision trees
• Python for Data Science • Bayesian learning
• Selected topics in data preparation/preprocessing • Neural networks
• Dimensionality reduction (e.g. PCA) • Deep neural networks (e.g. CNN,
• Clustering (e.g. k-means) RNN and LSTM)
• General introduction to supervised methods • Model evaluation
• Regression (e.g. linear, logistic) • Feature selection
• Classification (e.g. k-NN, support vector machines)
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 62. We have complemented their skills with off- and on-the-job teaching - #2
On-the-job (over 2 years)
Scientific advisors
• Professor for Data Science (University of Geneva) and the FSO’s deputy head of
methods have accompanied/supervised the five pilot projects and validate the results
from the scientific point of view.
Team of “Data Scientists”
• Key idea is to share/transfer the skills and the knowledge inside the FSO Organization.
• Trying to avoid an organizational split between “traditional statisticians” and “modern
statisticians or data scientists”.
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 7Agenda 1. What did we do ? 2. What are our experiences ? 3. What will be the next major step ? 5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 8
What are our experiences ? - #1
Hard skills
• Math & statistical skill, Technical skill and subject matter can be learned. These skills are
not always easy to acquire but it seems not to be the hard part of the game!
Up to 2020 we will integrate a standard curriculum “Data Scientist” in our internal teaching
program. We will collaborate more with Universities to define the exact content.
Soft Skills
• Soft skills (e.g. collaboration, creativity, problem solving, communication, story telling)
need a change in the mindset of all employees.
These skills are not so easy to teach… they primary need to be practiced on a daily basis
Up to 2020 we will open a new mandatory curriculum “Agile Organization”.
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 9What are our experiences ? - #2
Academic curricula
• Swiss Universities offer standards curricula in data science. The content of these curricula
often does not match with the FSO’s expectations.
FSO does not really need “Supermen or Superwomen” that can cover all the production
process on his own.
National Statistical Institute as employer
• Recruiting Data Scientist for a NSI likes FSO is not easy. Salaries are not so attractive
and the tasks that we can offer to a young data scientist do not offer the expected variety
and freedom that they are looking for.
FSO wants to empower its employees and not to replace them with Data Scientist!
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 10Agenda 1. What did we do ? 2. What are our experiences ? 3. What will be the next major step ? 5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 11
What will be the next major step ?
Version 2.0 of our Data Innovation Strategy
The FSO is currently defining a version 2.0 of its data innovation strategy for the years 2020
- 2023. The creation of an official Data Innovation Lab and a Competence Center for Data
Science will (probably) be at the heart of the new strategy.
Strategic objective 1: To create a central, cross-
departmental and independent "Data Innovation Lab"
(DIL) with a focus on data innovation services, i.e. the
application of “complementary analytics methods” to data
(and not to the type of data source and/or technology), for
the FSO (I), the whole Swiss public statistics system (II)
and the whole federal administration (III).
5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 12Questions & Answers 5th International Conference on Big Data for Official Statistics | Swiss Federal Statistical Office | Prof. Dr. Bertrand Loison | 3 Mai 2019 13
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