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Tetra Pak is a global food packaging and processing company with head offices in Lund, Sweden. The company offers packaging, filling machines and processing for dairy, beverages, cheese, ice-cream and prepared food, including distribution tools like accumulators, cap applicators, conveyors, crate packers, film wrappers, line controllers and straw applicators. Tetra Pak has undergone a digital transformation over the past years and strive to use all the latest and greatest digital technologies to deliver even more value to our customers. A Digital Transformation Program has been established to ensure that we maintain and extend our industry leadership by driving digital business development, developing digital products and services, and building internal capabilities.

In the role as Senior Data Scientist, you will belong to the Digital Transformation Program and be part of Tetra Pak´s Data Science Team. You will participate in various projects, influence business decisions and drive digital transformation at one of the largest consumer packaging companies in the world. This position will be placed in Lund, Sweden.

We are now looking for a Senior Data Scientist with a good balance in these three different profiles:

Technical: Experience developing deployment ready code with focus on robustness and efficient deployment.

.Strong coding skills preferably in Python
.Experience with ETL development and distributed databases and query languages such as SQL, PySpark, Scala and/or general map reduce computing
.Knowledge of common data structures and ability to write efficient code in at least one language
.Experience with Git
.Experience with implementing Statistical models or Machine learning models in production software.
.Experience or familiarity with deep learning techniques for time series and image analysis and natural language processing is a plus

Statistics & Mathematics: Knowledge of quantitative methods is important. From statistical inference to predictive and prescriptive modeling together with optimization skills. You have a strong algorithmic thinking and independent research ability.

.Analyze data with statistical rigor. Ensure accurate interpretation by combining business acumen with detailed data knowledge and statistical expertise.
.Build statistical models to uncover insights or effect changes
.Knowledge of common statistical models and machine learning models, i.e. understands what is going on "underneath the hood"

Functional: Good understanding of operational processes, KPI's and decision supporting systems. Mainly in areas like production, quality, maintenance, logistics and after-sales process (warranty). Complementary revenue management for pricing and marketing (customer insights).

.Translate analytic insights into concrete, actionable recommendations for business or product improvement, and communicate these findings.
.Drive efforts to enable independent interpretation of results through education, improved tools, and data visualization.

Additional requirements:

.Minimum experience of 4-7 years within Data Science projects
.Master or PhD in Physics/Statistics/Computer Science or similar numerical field
.Experience working with agile/SCRUM

Main Responsibilities:

-Participate in data science projects, be hands-on and build statistical models and determine optimal modeling approach for each business scenario
-Oversee junior data scientists
-Development, test, implement and deployment of data science solutions to solve various business issues,
-Work closely with Data Scientist Managers, Business stakeholders and subject matter experts to review expected outputs and applicability to business challenge
-Identify and take part in operationalization of valuable insights from the data into business and digital applications.
-Partner with internal/external stakeholders, product owners and team members and drive product development plans.
-Drive methodological innovations into data science and digital products in the different functional areas such as services, product development, supply chain, operations optimization and similar domains.

Who you are

As a person, you are a team player, honest and humble. You have exceptional interpersonal and communication skills coupled with strong business acumen. You must be able to translate business objectives into actionable analyses, and analytical results into actionable business and product recommendations. You have a passion for learning and innovating new methodologies at the intersection of statistics, applied math and computer science. Furthermore, you are a high-energy self-starter with passion for your work, put attention to details and have a positive attitude. Excellent written and verbal English skills are essential.

We offer

As our new Senior Data Scientist you will be part of a global leading company where our vision is to make food safe and available everywhere. We can offer you highly skilled and passionate colleagues, a vibrant melting pot of diversity, and a challenging and high paced work environment where our employees take great pride from protecting food to protecting the planet. You will work in a market leading company which offers continuous training and development opportunities in a trendy, comfortable and activity-based office environment. At Tetra Pak we believe in work-life balance, have flexible working hours, sports and training facilities, and nice canteen and offer an attractive pension and insurance scheme, incl. health care arrangements.

Care to join?

Please submit your CV and motivational letter in English before August 26th through our career site jobs.tetrapak.com

To know more about the position contact Data Scientist Manager Astrid Nielsen at +46 46 36 4595

Questions about your application contact recruiter Anna Jakobsen at +46 46 36 3747

For trade union information contact Sveriges Ingenjörer Mare-Charlitte Jeppson at +46 46 36 6121 and Unionen Annika Svensson at +46 46 36 3916

Detta är en jobbannons med titeln "Senior Data Scientist" hos företaget Tetra Pak och publicerades på webbjobb.io den 13 augusti 2019 klockan 20:04.

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