Big Data Machine Learning Engineer

posted on October 12, 2020

Job Description

Location: Cleveland, OH

Duration: Permanent

Responsibilities: 

  • Bachelor’s degree in computer science, electrical/electronic engineering or other engineering or technical discipline is required.
  • Minimum of 8 years of experience in IT and Big data software development is required
  • Minimum 3+ Predictive Analytics model implementation experience in production environments using ML/DL libraries like TensorFlow, H20, Pytorch, Sci-kit Learn.
  • Experience in using NLP, Bi/Visual analytics, Graph Databases like Neo4j/Tiger Graph is preferred,
  • Experiences in designing, developing, optimizing and troubleshooting complex data analytic pipelines and ML model applications using Spark, HDFS and other big data related technologies
  • Programming in Python, R or Scala using distributed frameworks like PySpark, Spark, SparkR
  • Working Knowledge in IDE environment/Tools like Jupyter, R Studio, GitHub, Docker, Jenkins
  • Solid knowledge of data warehousing such as Hadoop, MapReduce, HIVE, Apache Spark, as well as cloud base data storage: Google Cloud Storage with various formats (Parquet, JSON, ORC, Avro, delimited)
  • Solid understanding of databases such as DB2, Oracle, Teradata, MySQL, PostgreSQL
  • Extensive Experience with R and Python including language-specific and data science-oriented packages required.
  • Experience with Hadoop and Spark cluster, SparkSQL, Spark ML, and other third-party machine learning algorithms using Scala, PySpark and/or SparkR
  • Experience with Linux/Unix required
  • Exposure to Google Cloud services- GCP or any cloud environment.
  • Working experience on Apache Airflow
  • Experience in enterprise scale analytic solutions development and deployment with high performance, scalability, availability & reliability.
  • Certified Professional Google Data Engineer preferred
  • Candidate must be a self-starter and creative problem-solver with an innovative and curious mindset.
  • Must have a working knowledge of advanced technology uses cases in financial services including machine learning, interactive data visualization, cloud computing, and streaming analytics.
  • Strong communication skills and the ability to interact and collaborate with all levels of the organization.
  • A broad, enterprise-wide view of the business and varying degrees of appreciation for strategy, processes and capabilities, enabling technologies, and governance
  • The ability to recognize pain points within the organization, functional interdependencies and cross-silo redundancies. Those issues may exist in role alignment, process gaps and overlaps, and business capability maturity gaps
  • The ability to apply architectural principles, methods, and tools to business challenges
  • The ability to create capability portfolios and technical roadmaps addressing gaps
  • The ability to understand and recognize the economics of technology and the business goals
  • The ability to perform industry analysis and identify business and technology trends specific to the portfolio
  • The ability to visualize and create high-level models that can be used in future analysis to extend and mature the business architecture
  • The ability to assist business case creation and realization by aligning business goals to organizational capabilities
  • Strong situational analysis and decision-making abilities
  • Financial and/or Banking background preferred

 

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