Technology Stack
Last updated
Last updated
Build my tech skills based on those requirements (see below)
Python Basics
Do a Python Basic Course
Python Analytics (Pandas, Numpy, Scipy) + Visualization
.
Python + Biotech:
Do Python ML
ML Basics in Python with AWS
Databases / SQL
Messaging Kinesis / Kafka
AWS + ML:
AWS:
Build my domain knowledge
BioTech Degree based on MOOCs
Build my network
Check for Open Lab Equipment for myself (e.g )
Participate in Open Science
(from germany?)
OpenLab MUC
Syapse - Data
OneOme
We integrate genomics and clinical data on a single platform and allow doctors to share important treatment and outcomes information across a national network. Our customers manage more than 1 million active cancer cases at hundreds of hospitals across the US and Asia. Now, we’re racing to meet growing demand and bring precision cancer care to every patient, regardless of location or income. Because most cloud technologies aren’t HIPAA-compliant, we often build from the ground up. Our autonomous, feature-focused scrum teams work in two-week sprints and own projects end to end, while our domain-based guilds encourage collaboration across teams.
Infrastructure:
Runtime: Docker on Kubernetes
Cloud platforms: AWS (preferred), Google Compute, Azure
Cloud orchestration tooling: Terraform, CloudFormation, SaltStack, Ansible
CI/CD: Jenkins, CircleCI
Infrastructure Monitoring, Application Performance Monitoring: Appdynamics, New Relic, Sumo Logic
Memory cache solutions: Memcache, Redis
Message Queueing: Kafka, Kinesis, RabbitMQ, Amazon SQS
Proxies: NGINX and related technologies is a plus
Frontend:
JavaScript, HTML5, and CSS3
Optimizing the performance of complex Javascript applications
Experience of building advanced dashboards is a plus.
Modern thick-client architecture (e.g. lightweight MVC)
Frameworks: React.js and Redux
Programming:
Languages: Python, Java, Shell scripts
web application performance tuning (all layers) and high availability architectures
Able to write, manage, debug multi-threaded asynchronous code with call-backs.
architect web solutions addressing SLA monitoring, security, performance, caching, debugging
building products using distributed technologies
Architecture: Understanding of micro services architecture/Containers using Docker, Kubernetes
Knowledge of distributed systems scaling, optimization, sharding, fault tolerance, and operation.
Data Analytics:
use most of AWS Compute and storage services along with PostgreSQL RDS, Aurora, DynamoDB, Redis, Elastic Search, Kinesis, Redshift
database administration tasks such as database installation, replication, database backup, restore and database maintenance
Write automation scripts for customer dataload jobs and scheduling of jobs.
scripting skills in Python (preferred), or other scripting languages (Bash, Perl, etc.).Rock solid Linux skills.
Basic DBA skills (e.g. MySQL, PostgreSQL). Exposure to administering NoSQL systems is a plus.Build automation experience is a plus
Log aggregation experience using Splunk/Sumologic/Logstash/Elasticsearch
Experience with visualization software (e.g Tableau, SpotFire etc)
Expert understanding of relational, NoSQL, and graph databases is a plus.
Experience with Kafka, Spark, database internals, transactions, query processing and optimization, as well as federated data systems is a huge plus.
Expertise in data science or machine learning, especially supervised ML algorithms, clustering, or natural language processing
Knowledge of hierarchical, relational and unnormalized data formats
Strong and demonstrable experience with more than one of the following:
Relational Stores (E.g Postgres, MySQL, Oracle)
Columnar or NoSQL Stores (Redshift, Cassandra, DynamoDB)
Graph Stores (Neo4J, Titan, Triple/RDF Stores)
Document Stores (Postgres JSONB, MongoDB)
In memory stores (Redis, memsql)
Distributed Processing Engines (Apache Spark, Apache Storm, Celery)
Distributed Queues (Kinesis, Apache Kafka, RabbitMQ)
Worked with multiple types of databases, including both relational and non-relational
Expert in SQL for extraction, querying and handling large amounts of data
Domain
Knowledge of healthcare datasets
Sensitivity to healthcare data
Having worked in regulated industry
Tech:
Fluent in Python and SQL
creating tools for others
Pandas, Numpy, and Scipy
AWS Redshift
data visualization tools (Looker, Domo, QuickSight, or similar)
Experience with Data Science
Understanding of Biology and/or Chemistry
Experience with data from instrumentation design / development
Previous experience in the Biotech domain
Experience with manufacturing data
Fluent in Python / Javascript
Experience with backend technologies such Django / Flask
Experience with one or more current JavaScript frameworks (e.g. Angular, React, Meteor)
Expertise with ES6
Fluent with Bash
Fluency with Linux
Familiarity with Nginx or Apache configuration
Strong skills in Python/Java/R
Deep theoretical understanding of Machine Learning and Statistics (Supervised/Unsupervised/DeepLearning/NN/Weak Prediction Model Ensembles/Genetic Algorithms)
Experience in TensorFlow, Keras, NumPy, etc
Experienced in BigData and its tools (e.g. Hadoop MR/EMR/Spark) is
BSc/BA in Health Informatics, Information Management, Statistics or relevant field.
Proficiency in SQL, Kafka, Map-Reduce, and other data warehouse solutions
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Python, Flask, Pytest, React/Redux, Docker []
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