DATA SCIENTIST

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EASE Defined: Entrepreneurs, Adopting, To Serve, Each Other

EASE offers A predictive freelance management system that gives organizations access to a tailored and screened pool of on-demand remote talent.

JOB DESCRIPTION: Ease is seeking Data science to support our client's research and development needs. As a Data Scientist, you will be a part of Digital Transformation team solving complex business problems using data and analytics-driven approach. In this role, you will be responsible for analyzing structured and unstructured datasets, perform data wrangling and feature engineering, devise innovative data science solutions and build production-ready models. You will work in a cross-disciplinary team comprising data engineers, software developers, and product champions among others.

REQUIREMENTS : 

• You have 4+ years of experience as a Data Scientist in a medium to large organization, with a proven record of analysis and research that positively impacts your team.
• You have superior knowledge of statistical analysis methods, such as input selection, logistic and standard regression, random forests, etc.
• You have extensive experience with pandas, NumPy, and sklearn. Experience with deep learning frameworks (TensorFlow, Keras, PyTorch, or similar) is a plus
• You are capable of working with engineers to build an actual production system that uses machine learning and artificial intelligence. We don't expect you to write production-quality code, but you should have some programming experience.
• You are comfortable with at least “medium data” technologies and how to transcend the “memory-bound” nature of most analytics tools.
• You possess excellent SQL/relational algebra skills, ideally with at least a basic knowledge of how different types of databases (e.g.: column vs row storage) work.
• You possess excellent communication skills and the ability to clearly communicate technical concepts to a non-technical audience.

SKILLS: Data Science, Python, Machine learning, ML, R programming language, R, Data Reporting, Data modeling, MySQL, Tensorflow, Pandas, Data Analytics, Statistical analysis, statistics, Linear regression, A/B Testing, Natural Language Processing, Deep Learning, Big Data, NLP, Wrangling, Data Wrangling, OOP, Java, Julia, Scala, MongoDB, MATLAB, SQL Server, Oracle, IBM DB2, PostgreSQL, NoSQL databases CouchDB, DynamoDB, HBase, Neo4j, Cassandra, Redis, Pytorch, Keras, Amazon Web Services, AWS, Windows Azure, Google Cloud, IBM Cloud, Microsoft Excel, Ph.D., “Master's degree in statistics”, computer science, C, C++, C#, Perl, SQL, SAS, Hadoop, Spark, Hive, Pig, AI, Artificial Intelligence,