Welcome to Adam's freelance profile!
Location and workplace preferences
- Amsterdam, The Netherlands
- Remote only
- Primarily works remotely
- Project length
Would prefer to avoid:
- Between 3-6 months
- ≥ 6 months
- ≤ 1 week
- ≤ 1 month
Freelancer code of conduct signed
Read the Malt code of conduct
Native or bilingual
Adam in a few words
Senior Data Scientist - As a freelancer
Randstad - Randstad
Data Scientist - As a freelancer
Technologies: Python, Tensorflow, Pytorch, SageMaker, PySpark, Airflow, XGBoost, Learning To Rank algorithms, S3, Jira, Apache Tika, Transformers (BERT). AWS.
Travel & Tourism
Senior data scientist
Built and maintained the whole data platform with ETL, Redshift and Looker. The processes were all still running smoothly 1 year after I left.
Improved conversion rate by +10% by implementing a recommendation engine
Improved the ranking algorithm by segmenting users leading to +56% in revenue
Developed multiple dashboards that were used on a daily basis by business stakeholders
Coached our business users on how to use the data platform
Technologies: Python, Redshift, MariaDB, SQL, Sklearn, Implicit feedback recommendations, Cron, Markov Chains, Looker & Tableau, S3. AWS.
Logistics & Supply Chain
Technologies: Python, S3, Airflow, Sklearn, Keras, LSTM, BigQuery, PostgreSQL. AWS.
Created a capacity model for the CDN across Liberty Global's footprint
Designed and implemented a performance prediction tool based on Clustering and trend analysis
Developed a versatile and easily extendible API to support our visualisation tool
Prioritised and organised the team work in accordance to business needs
Carried Impact Assessments on CDN prior to product launches and upgrades
Technologies: Python, Flask, Pandas, R, Elasticsearch, Jira, Confluence, Github, R Shiny, Kafka.
Technical data analyst
I setup and maintained a 7 node Elasticsearch cluster
I helped with debugging issues on a Cloudera Big Data platform
I setup and maintained a 3-node Apache Flume setup
Created multiple dashboards on Kibana and data analyses using R and Python. These were used to inform product development and prioritisation of next features
Technologies: R, Shiny, Hive, Elasticsearch, Python, Apache Flume, Hadoop, Elasticsearch, Excel
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