Data Science | Data Engineering | Machine Learning / AI / Computer Vision | Data Analytics | Database
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Motion teams dedicated to Data recruiting deeply understand this tech sector and — more importantly — deeply penetrate their local marketplace to create rich and relevant networks with a focus on the following disciplines:
Python, R, SQL
Spark, Hadoop, MapReduce, Hive, Pig, Kafka
TensorFlow, Caffe, Keras, Theano, PyTorch, Scikit-learn, OpenCV, MATLAB, CUDA, PCL, Dlib
Business Intelligence, Data Visualization, ETL, Data Warehousing
NoSQL, MySQL, PostgreSQL, SQL, Oracle
Recruitment trends are the backbone of how we work. Our teams research and share local marketplace intel as part of our everyday routine and data-driven approach to produce results.
Open Jobs per Candidate
Annual Change in Market Demand
Top Employing Geography
One of the major trends we are seeing within the data engineering marketplace is the emphasis on experience with scalability. Not only do employers want to see this contextual litmus test of scalability within a new hire’s skill set, candidates also are seeking out this key attribute in the roles they want most. Real-time consumption of data specifically is the goal, and strategies like live vs. batch streaming are dependent upon highly intelligent data teams.
You have to be careful when recruiting for data engineers or it simply ends up being a hunt for buzzwords — Hadoop, Spark, MapReduce, Kafka, etc. More often than not, this fails to net a match. It’s never just WHAT data technology is being used, but rather HOW (batch processing, data streaming), WHY (visualization, real-time analytics, BI reporting), and WHERE (third parties, internal metrics, user metadata) it’s used that unlocks the true set of capabilities and value of a candidate.
AI & ML models are built on historical data, but due to global shifts in today’s market, these models may be making predications based on previously unseen conditions. Watch Tech in Motion’s panel of experts discuss what tech leaders need to keep in mind during this ever-evolving climate.
With the need for Data Science and ML professionals up by 50% across several industries in 2020, we sat down with VP of Data Science, Lacey Plache, to discuss how the two teams can best integrate together.
See how we helped a Fortune 500 Banking Company find Senior Big Data Engineers, Senior Java Engineers and Scala Engineers near Washington, D.C.