Dr.-Ing. Martin Franke

Data Scientist / Solution Specialist with nearly ten years of experience in interpreting and analysing data for

driving and optimising conversions. Holding a doctoral degree in applied advanced machine learning techniques.

Proficient knowledge of statistics and analytics from computer science and psychology. Excellent understand-

ing of using state-of-the-art technology to tackle challenges and present significant solutions.

ACADEMIC QUALIFICATIONS PERSONAL DATA

Doctors Degree -

Dr.-Ing. in applied machine learning techniques

Diploma -

Computer Science with minor Psychology

Year of birth: 1988

Nationality: German

MAIN EXPERTISE LANGUAGES

Lean and appropriate data analysis for

applied automation techniques.

German (native language)

English (fluent)

Dr.-Ing. Martin Franke

TECHNOLOGIES

Programming Python, Scala/Java, SQL

Statistics / ML Python, SparkML, Pandas, scikit-learn, MXnet

Databases PostgreSQL, Google BigQuery, Amazon Redshift, MySQL, S3

Reporting Jupyter, Zeppelin, Databricks

Cloud Google Cloud, AWS, Zapier, Databricks

METHODOLOGICAL

Data analysis

Data modeling

Predictive Analytics

Real-time Analytics

Stochastic Modelling

Deep Learning

Recommendation Systems

Cost-optimized applied machine learning techniques

INDUSTRIES

Research and Development

Media and Television

Content Publisher

Ecommerce

Automotive

Dr.-Ing. Martin Franke

03/2019 - 12/2019 Automotive

ESG Mobility GmbH provides solutions for complex electronic and IT systems, especially as an automotive

supplier for the AUDI AG, Ingolstadt. The project goal is to develop a platform for automated statistical

analysis of driving behaviour regarding assistance systems and errors. To reach this, sensor data from

different BUS systems are combined with user generated data and unified in a Big Data Platform. In this

platform it is possible to detect common patterns resp. behaviour for further analysis or automated re-

actions.

Role Data Scientist

Technologies Scala, Python, Apache Spark, AWS, SparkML, MXnet

04/2018 - 02/2019 Health Care

BODYVISER GmbH provides digital, mobile solutions, to tackle chronic stress and find inner balance. For

personal assistance, it is also possible to find the right expert on the platform right away. The BODYVISER

platform serves mobile coaching, digital therapy assistance for experts and clients. Based on insights

and findings out of the therapy process, an adaptive lifestyle is established according to individualised

needs.

Role Cofounder / CTO / Data Scientist

Technologies Scala, Python, Apache Spark, AWS, SparkML, Deeplearning4j

Dr.-Ing. Martin Franke

02/2018 - 04/2018 Content Publisher / Ecommerce

Social Media Interactive GmbH with its brand BodyChange is with over 450.000 customers the top growing

online fitness brand in the DACH region. The project goal was to get a unified view of Newsletter, Shop and

so-called Coaching data. For this, a new data warehouse layer for big data sources has been accomplished.

With this data, it is now possible to answer data-centric questions such as churn rates, retention rates,

trending products, and product recommendations. As a new data-driven company, Social Media Interactive

GmbH is now capable finding best marketing strategies.

Role Data Scientist

Technologies Python, Amazon Redshift, Postgres, Zapier, Matillion ETL for Redshift

05/2017 - 12/2017 Content Publisher

Social Sweethearts Gmbh is the leading global digital publisher of individualized content. This content

consists mainly of fortune telling quizzes for Facebook users. The project goal was to optimize answers

for these quizzes by enhanced user targeting. Additionally, conversion rates, especially the share rate on

Facebook, increased by building precise user models combined with recommendation techniques. A higher

share rate, in turn, results in a higher page, and therefore, ad impressions.

Role Role: Data Scientist

Technologies Python, Google BigQuery, scikit-learn, Matillion ETL for BigQuery, Zapier

Dr.-Ing. Martin Franke

06/2016 - 04/2017 Enterprise Search

IntraFind Software AG develops products and solutions for easy searching, finding, and analyzing of

structured and unstructured information across all available data sources of a company. The project

goal was to develop methods for relevance score shaping in these search engines. In contrast to the exis-

ting approach, relevant items should be found not only by the keyword but by taking user-centric know-

ledge into account. For example, my own search history, the search history of my departement and also

company-wide announcements shape the importance of the result items.

Role Data Scientist

Technologies Python, Scala, Apache Spark, elastic Stack

07/2015 - 06/2016 Media and Television

The inovex GmbH acts as a service provider for the ProSiebenSat.1 Media SE. The goal for the longtime pro-

ject was the to migrate the data warehouse from PostgreSQL basis to the Apache Hadoop stack. To achieve

all objectives, an ETL process with more than 30 data sources, incl. Google Analytics 360, Facebook API,

Mixpanel, Webtrekk, was maintained. With this in mind, it became possible to extract and calculate busi-

ness-critical key performance indicators irrespective of data source borders.

Role Data Scientist

Technologies Python, Scala, Apache Spark, Pentaho, Apache Hadoop, PostgreSQL

Dr.-Ing. Martin Franke

09/2012 – 04/2016 Research / Health

Regular daily routines not only increase the overall well-being but also affect peoples’ health and the

perceived stress level. Large discrepancies in these rhythms may result in sleep disorder up to chronic

depressions. Nowadays, daily routines can only be manually supervised by experts in order to avoid these

negative consequences. The intention of the proposed solution is to offer automated and preventive assis-

tance for this complex process. This is done, by combining several sources of information, e.g. domestic

sensor values, smartphone data, social networks, fitness trackers, to determine daily activities with

machine learning techniques. In the end, calculated routines from daily activities result in patterns, out-

liers, and corresponding causes.

RolE Research Associate

Technologies Java, Python, WEKA, nodejs, OWL