Risk Focus

Senior Data Scientist

Job description

Risk Focus, a Ness Company, provides strategic IT consulting to global enterprises. Our DevOps and Infrastructure practice provides solutions, methodologies, and strategic guidance for digital transformation, containerization, and automation. Our Financial Services team offers strong domain expertise and technology acumen to deliver feature-focused solutions in Capital Markets.

We solve complex business problems with technology and insight. Our business domain knowledge, technology expertise, and Agile delivery process have delivered seamless Digital Transformations at some of the largest customers globally. We’re an AWS Advanced Consulting Partner, a Premier Confluent Systems Integrator and a Snowflake Select Services Partner.

As a Senior Data Scientist you will:

  • Be a technical and team leader on data science projects for Ness clients.
  • Be able to lead a project team in all aspects of a data science project:
    • System architecture
    • Data cleansing
    • Data wrangling
    • Feature generation and selection
    • Model development and testing
    • Deployment
    • Mentoring junior team members
    • Communications with clients about project scope, schedule, and requirements
  • Provide both pre-sales engineering as well as post-sale project delivery

Requirements

  • Strong Python skills (Numpy, Pandas, Scikit-learn, etc)
  • Strong quantitative skills
  • Experience with data collection, cleaning, and ETL processes
  • Experience with commonly used machine learning algorithms
  • UNIX/Linux skills including shell scripts and system administration
  • Track record of delivering and leading data science projects
  • Excellent verbal and written communication skills
  • Ability to manage multiple projects simultaneously

Additional Desired Skills

  • Relational database skills (SQL, data modeling, ETL)
  • Experience with machine learning projects on AWS and/or Azure
  • Programming languages including Java, Scala, C++, C#, JavaScript, R
  • Data warehouse technologies such as Snowflake, AWS Redshift, and/or Azure Synapse Analytics
  • Experience with AWS ML technologies such as SageMaker
  • Knowledge of deep learning, NLP or big data analytics tools (e.g., Apache Spark, DataBricks) is a plus
  • Experience with streaming data analytics, Kafka, and/or Kinesis Streams

Education and Certification Requirements:

  • An undergraduate degree in a STEM discipline is usually required.
  • Graduate degree (MS or PhD in Data Science, Statistics, Applied Math, Computer Science, or other quantitative discipline) strongly preferred
  • AWS or Azure certifications desirable (Solution Architect, Machine Learning or Big Data specialty certification
  • Snowflake SnowPro certification desirable

Benefits

  • Flexible work environment with a globally distributed team
  • Competitive compensation packages including performance bonuses
  • Paid vacation and sick time off
  • Employer-subsidized medical, dental, and vision insurance
  • Company-paid short- and long-term disability insurance
  • A culture of cooperation and support
  • Continual professional and personal development through employer-paid training and certifications

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