Sr Data Scientist

Position Accountability/Scope:

The Senior Data Scientist and Engineer is responsible for/ helps delivering targeted business impact per initiative in collaboration with key stakeholders. He / she works on end-to-end data management that will enable faster, better and more informed decision-making within the business and help create business value out of data & analytics.

Core Job Responsibilities:

• Help build and maintain a close contact to key business stakeholders and relevant communities

• Build effective and efficient Advanced Analytics solutions to business needs, leveraging available market resources as much as possible

• Help derive and continuously refine AA guidelines and standards through synthesizing learnings from prioritized AA initiative (“learning while doing and driving impact”).

• Work with key stakeholders within the company to help model their data landscape, obtain data extracts, and define secure data exchange approaches • Help plan and deliver secure, good practice data integration strategies and approaches

• Help acquire, ingest, and process data from multiple sources and systems into Big Data platforms

• Help create and manage data environments in the Cloud

• Collaborate with our Data Scientists and engineers to map data fields to hypotheses and curate, Page 2 of 2 wrangle, and prepare data for use in their advanced analytical models • Ideally, have a strong understanding of Information Security principles to ensure compliant handling and management of client data wrangle, and prepare data for use in their advanced analytical models

• Ideally, have a strong understanding of Information Security principles to ensure compliant handling and management of client data

Minimum Education:

• Master in relevant field (e.g., applied mathematics, computer science, electrical engineering, applied statistics)

Minimum Experience/Training Required:

• At least 4 - 6 years of relevant working experience in larger companies or corporates, ideally in pharma environment

• Good /solid experience working on full-life cycle data science; experience in applying data science methods to business problems (experience in the financial/commercial or manufacturing / supply chain areas a plus).

• Proven ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets • Strong experience in multiple database technologies such as: Distributed Processing (Spark, Hadoop, EMR) Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL) MPP (AWS Redshift, Teradata) NoSQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan)

• Strong experience in e.g., data mining, statistical modelling, predictive modeling and development of machine learning algorithms

• Practical experience in deploying machine learning solutions

• Programming experience in R or Python and ideally also in object-orientated programming such as e.g., C, C++, Java

• Good understanding of good software engineering principles

• Good knowledge of testing frameworks and libraries

• Strong experience and interest in Cloud platforms such as e.g., AWS

• Proven problem-solving ability in international settings

• Result-oriented analytical and creative thinker with strong background in analytics and statistics

• Proven communication skills

• Intrinsic motivation to guide people and make Advanced Analytics more accessible to a broader range of stakeholders. Ability to work with cross-functional teams and bring business and data science closer together - consultancy experience a plus

• Fluency in English a must, additional languages a plus