DAT Solutions is looking for a Manager, Data Science to join our team in Denver, Colorado or Beaverton, Oregon.
The Data Science team at DAT builds machine learning and analytical tools to integrate into DAT products across all the companies product lines. We work closely with our engineering, product management, and business intelligence colleagues on a wide variety of projects, including forecasting, recommendation systems, search, anomaly detection, historical benchmarking, and many others.
The Data Science (DS) team leads directly to new products, enhancements to existing products, and new internal tools, such as decision support and advanced business intelligence products.
What You’ll Do
- The data science engineering team is responsible for building, designing, and maintaining systems which:
- Train new models replicably and reliably, and adding them to our growing catalog of models
- Evaluate past models against new data
- Host models as microservice APIs for consumption by other internal engineering teams
- Apply models in large overnight batch jobs to output data into S3 and/or Database tables.
- Building and maintaining a library of common code tools to support data scientists in both research and engineering roles.
- The engineering manager is ultimately responsible for the direction, execution, and quality of all activities undertaken by their team. They organize and prioritize engineering tasks and deliverables, and make sure changes, releases, and timelines are communicated to all stakeholders, such as other data science team members, engineers, and product managers.
- Work closely with the other data science research and engineering managers and leads in order to coordinate work across the broader Data Science family of teams, ensure research hand-offs to their team are well-organized and thoughtfully executed.
- Ownership of the quality of all existing ML engineering products. Ensure rigorous testing, evaluation, and monitoring is in place for all of the team’s products.
- Organize the team’s day-to-day and week-to-week tasks, update timeline estimates early and often, and communicate clear, concise project updates to senior and executive leadership teams.
- Organizing the DS Engineering team’s on-call schedule and culture, ensuring that everybody feels empowered to help, while not overwhelmed by unbalanced responsibilities. Training and supporting newer team members to help share the load with more experienced members will be key.
- Work closely with downstream stakeholders to communicate project updates and changes.
- Identify and make recommendations on new tools and technologies to enhance the team’s capabilities and efficiency.
- Provide team members with education and professional support opportunities to support their continued growth and development.
- Mentor and guide team members in all areas of Data Science, including research acumen, engineering best practices, applications of research to business needs, and professional communication.
The Skills and Experience You’ll Need
- Requires a minimum of 6 years of related experience with a Bachelor’s degree; or 3 or more years’ experience with an advanced degree; or equivalent experience
- At least a year of management experience in data science, or an analytical research field using the same tools and platforms, OR at least two years of informal leadership in a data science business environment, such as an engineer, lead, or principal who focused on machine learning products.
- Sufficient knowledge of cloud-based data science tools to lead the team in using those platforms and capabilities. Coaching team members who fall back on local computation to use available cloud resources for most use cases.
- Professional Python developer with sufficient skill to review and mentor other researchers in Python best practices within the realm of the data sciences.
- Sufficient knowledge of cloud-based data science tools to lead the team in using those platforms and capabilities, and design new cloud-native ML systems to power our products.
- Experience using and writing some Infrastructure-as-Code, especially Terraform for AWS.
- Experience delivering machine learning models and model outputs as business products.
- Experience delivering machine learning products or research results which are used by and relied on by other engineering or business teams
- Well-versed in many industry-standard machine learning, forecasting, and statistical techniques
For Colorado-based candidates, in compliance with Colorado's Equal Pay for Equal Work Act, the minimum salary for this role is $165,000.00 + benefits. The maximum compensation for this role can vary significantly depending on your job-related skills and experience. DAT considers factors such as scope and responsibilities of the position, candidate's work experience, education and training, core skills, internal equity, and market and business elements when extending an offer.
DAT embraces the value of a diverse workforce, and believes it is a core strength of our company that we encourage those values in every DAT employee, at every level of our organization, regardless of tenure or rank. We provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)