Data Scientist II

Machine Learning, Data Science, Graph Theory, Predictive Models, Deep learning, Data mining, SaaS, Natural language processing, Algorithms, Text mining
Full Time
Depends on Experience
Work from home not available Travel not required

Job Description

At Interos, we are disrupting the way Fortune 500 companies and government agencies identify and respond to risk within their supply chains – whether this risk is being caused by cyber breaches, geopolitical issues, malicious intent, quality concerns, natural disasters or unethical sourcing and sustainability concerns. We deliver the data and insights to business leaders that help them identify, visualize and understand the ripple effects that could impact their supply chains, before they happen.

Recently funded by Kleiner Perkins and pivoting to an automated solution, Interos is in essence, a start-up SaaS environment. We need someone who thrives as part of fast-paced team and takes pride in their attention to detail, their ability to take on many different things.

The Opportunity: We are looking for an experienced Data Scientist with exceptional product sense to develop machine learning and deep learning models and algorithms that create unique insight for customers. The ideal candidate should be someone who can automate scoring using machine learning techniques, build recommendation systems, and select the correct data points for analysis from the large open source and proprietary data sets. The ideal candidate must have strong experience using a variety of data mining/data analysis methods and tools. You are focused on results, a self-starter, and have demonstrated success for using analytics to drive the understanding, growth, and success of a product.

Key Responsibilities:

  • Analyzing large data sets to identify actionable insights
  • Designing and deploying deep learning algorithms and predictive models
  • Developing custom data models and algorithms to apply to data sets
  • Assessing the effectiveness and accuracy of new data sources and data gathering techniques
  • Developing processes and tools to monitor and analyze model performance and data accuracy


  • Degree in Computer Science, Statistics, Applied Mathematics, Computational Linguistics, Artificial Intelligence or related areas preferred
  • 4-6 years of hands on working experience in one or more of the following areas: Natural Language Processing, Machine Learning Models, Question Answering, Text Mining, Information Retrieval, Distributional Semantics, Data Science, Knowledge Engineering
  • Experience in productization of machine learning algorithms and the ability to deliver data science components that are part of successful commercial products
  • At a minimum a working knowledge of NLP, Graph Theory, and Network Analysis
  • Fluency in one or more programming languages (Python, Java, R, etc.)
  • Experience with statistical data analysis, experimental design, and hypotheses validation
  • Readiness to collaborate with engineering teams to develop prototypes and software products


  • Comprehensive Health & Wellness package (Medical, Dental and Vision)
  • 10 Paid Holiday Days Off
  • Accrued Paid Time Off (PTO)
  • 401 (k) Employer Matching
  • Stock Options
  • Career advancement opportunities
  • Casual Dress
  • Hackathons
  • On-site gym and dedicated Peloton room at headquarters
  • Company Events (Sports Games, Fitness Competitions, Birthday Celebrations, Contests, Happy Hours)
  • Annual company party
  • Employee Referral Program


Interos is proud to be an Equal Opportunity Employer and will consider all qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity, genetic information, national origin, disability, protected veteran status or any other classification protected by law.

If you are a candidate in need of assistance or an accommodation in the application process, please contact

Posted By

Lisa Makings

Dice Id : 91007501
Position Id : 6276107
Originally Posted : 2 months ago
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