Lead Data Scientist

Rackspace is a hosting company based in San Antonio, Texas that prides itself in providing industry-leading customer support ad hosting value for those that are making the logical move to managed computing. We are growing rapidly due to our past successes (delighted customers), business model, and excellent customer support. We are looking for highly-motivated, competent individuals that can help propel us to the next level.

The Rackspace Private Cloud (RPC) team is looking for an experienced Data Scientist who's adaptable and can help us understand and solve our business problems. We need a great communicator that can work with our team and customers to help ensure that everyone understands the data, and the insights we're deriving from it.

As a member of the RPC Operational Fabric team, you'll work with software developers, SREs, and stakeholders to help us transform RPC into a data-driven organization. You'll do this by helping our team understand the existing data, asking the right questions, gathering the right information, and building models and self-service reports to help our business leaders make sound data-driven decisions about how to scale and operate our organization.

Responsibilities

• Collaborate with data experts to identify the most valuable KPI data and reports that would enable business stakeholders to make the most informed decisions.
• Enable operations to drive towards the goal of zero downtime.
• Develop a deep understanding of the business and its most important data.
• Collaborate with Data Engineers on Data Pipeline design/development to ensure data recency, breadth and accuracy.
• Help facilitate and standardize data quality across data stores.
• Facilitate mentoring and sharing of Data Science / Machine Learning techniques and solutions to local teams as well as the Data Science Community in general.
• Attend team meetings, communicate often regarding status, and be the go to person on the team for Data-related issues. 

About Us

• Team Size: Currently 8 senior developers/engineers and a technical manager.
• Hours: We have flexible working hours within our 40 hour work .
• Location: US/UK work from home and offices in US/UK (most states supported).
• Travel: About once or twice a year for a conference or team gathering.

It's important to go into a job understanding what you'll be working on, and what skills you need to be successful. At a high level, we're looking for folks who can jump right into the middle of our data, sit down with customers, and start understanding how to build models and create reports in order to help our team make more data-driven management decisions.

Required

• Bachelor’s degree in statistics, mathematics, or a technology-related field plus 7 years of work experience in hands-on statistical and data analysis and programming with some managerment experience

• Strong experience in machine learning techniques (unsupervised, supervised, reinforcement, demonstration, etc.) and optimization algorithms that include statistical analysis techniques such as Grouping, Clustering, Linear Regression, Stochastic Gradient Descent, Principal Component Analysis as well as Recurrent and Convolutional Neural Networks.
• Familiarity with Basic SQL.
• Proficiency with at least one programming language like Python or R, to a level where you are comfortable writing a complete stand-alone applications for Exploratory Data Analysis (EDA) to implementing full models.
• Familiarity with data architecture, specifically data pipelines and data warehouses/lakes.
• Familiarity with big data tools like Spark, Hadoop, Kafka, Cassandra or their cloud equivalents.

Additional

In addition to the key skills listed above, here are some other skills that you'll likely be using on a regular basis. We don't expect everyone to have all of these skills, but exceptional candidates will have experience with, or be excited to learn :

• Understanding of SQL and no-SQL databases and the ability to read, write and optimize complex queries.
• Knowledge of business analytics, and comfort working with stakeholders using common business terminology.
• Familiarity with interactive notebooks to communicate your work such as iPython, Jupyter or Google DataLab.
• Familiarity and experience with deep learning tools and techniques using tools such as Keras, TensorFlow, Theano, etc.
• Familiarity and experience with Natural Language Processing (NLP) and text data mining.
• Familiarity with data visualization, including proficiency with at least one data visualization framework such as Tableau, Looker, Canvas, Processing or D3.
• Experience working on software development projects and with common Software Development Lifecycle patterns such as Agile/Scrum/Kanban.

Supervision

We're a helpful and supportive group, and we're not going to leave you without a clue of where to go or what to do. That said, we're looking for senior level individuals who can demonstrate a high degree of autonomy and provide self-direction. After all, you'll be the domain expert in your area.

• Operate with little or no direct Supervision.
• Work with stakeholders and customers inside of Rackspace to set priorities and goals.
• Self-organize with other team members to deliver customer value.

Experience and Education

There are a lot of ways to get experience. Hands on work and education are both great ways to learn what you need to do for the job. We're looking for someone who has an advanced degree in Statistics, Physics, Mathematics, Computer Science or another technology-related field, as well as 7+ years of hands-on experience working with statistical, data analysis and Machine Learning.

Additional Info – for GitHub only

Contact

Please email your resume/github/linkedin (your choice!) to Jesse J. Cook. No agencies or recruiters please.

Equal Employment Opportunity Policy

Rackspace is committed to offering equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic.

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