Data Science Engineer

Silicon Valley, CA, United States

Lattice Engines


Role Location

  • Silicon Valley, CA, United States

Employees

501+ people

Address

1820 Gateway Dr Ste 200
San Mateo, CA, 94404, US

Tech Stack

  • Redshift
  • Redis
  • Zookeeper
  • Kafka
  • Akka
  • DynamoDB
  • Docker
  • Node.js
  • Numpy
  • SciPy
  • Scikit-Learn
  • Tensorflow
  • Hadoop
  • Cascading
  • AWS
  • React
  • Apache Spark
  • Neptune
  • Java
  • Spring MVC
  • Terraform
  • MySQL

Role Description

We are looking for talented Data Engineers who want to transition into a combined Data Science and Data Engineering role as a member of the data science team. This central role will include a range of responsibilities. Part of the role will be to participate in groundbreaking R&D projects to leverage massive structured, unstructured, transactional and real-time data sets from a variety of sources. Central to the role will be to drive the productization of these insights and their delivery to the Engineering team. At the end of the day, we analyze customer usage patterns and make actionable statistically robust recommendations that are impactful to real world businesses.

Required qualifications: • Advanced degree in a quantitative discipline with a preference for computer science • Significant production level programming experience in most of the following: Java, Python, AWS, Hadoop (Hive, Pig, Spark), noSQL, UNIX/LINUX • Strong Java development expertise in building enterprise techniques for large scale distributed system design and big-data processing • Strong experience working with data and data products, include: data analytics/transformation/aggregations/sampling/deduping/bucketing/profiling etc. • Strong analytical and problem solving skills. Ability to hit the ground running and learn/adapt quickly • Excellent written and leadership skills. Team player

Desired qualifications: • Strong development experience in Python • Strong understanding of information retrieval concepts, machine learning, natural language processing • Good understanding of metadata driven system/workflow • Good understanding of system configuration management, container technologies and configuration bootstrapping • Desired hands-on experience with Docker, Hadoop, Cascading, Spark, AWS, DynamoDB, Redshift, Redis, Akka or similar technologies • Good understanding of HTTP and webservers, and operating public APIs in MicroServices environment

About Lattice Engines

Dun & Bradstreet has the world’s most comprehensive business data sets and analytics capabilities to power today’s most crucial business needs. That’s why 90% of the Fortune 500, and companies of all sizes around the world, rely on Dun & Bradstreet to help grow and protect their business. Our engineering teams focus on developing industry-leading, highly scalable, SaaS based applications to put this data into action. We are solving extremely intellectually interesting problems using machine learning, artificial intelligence and high-performance distributed computing.

We are looking for individuals interested in building world-class SaaS applications and solving complex challenges with one of the world’s largest B2B data sets. We have a supportive team atmosphere, using the latest technologies, and always strive to ensure D&B is the best place to learn and grow your career.

Our leading SaaS B2B Product, D&B Lattice, is an early innovator in the hottest area of big data applied to predictive marketing. We combine thousands of data signals from our customers and partners, and extract key business insights using a variety of machine learning, ranging from random forest to deep learning, to better understand business drivers behind each purchase decision. Our innovative marketing and sales application predicts: who will buy, what they are likely to buy, and when.

Company Culture

Building a forward-leaning culture where people come first: Now, more than ever, we're focused on building a strong and supportive culture where people feel empowered, aren't afraid to fail, bring their true selves to work, and take time to recover when needed.

A few examples:

We eliminated layers and flattened the structure of our organization so that our leaders are approachable and more in tune with our people. Our 'Sustainable High Performance' program offers resources and support to our employees in 4 key areas to support personal growth: movement, mindset, nutrition and recovery. Dress For Your Day: We evolved our approach to our dress policy. We wear what makes sense for our day.

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