Data Science Specialist
DataDirect Networks Inc - columbia, MD
Apply NowJob Description
Data Science Specialist Job Locations US-MD-Columbia Job ID Name Linked Office: Columbia Country United States City Columbia Worker Type Regular Full-Time Employee Posting Location : State/Province MD Overview This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing. "DDN's A3I solutions are transforming the landscape of AI infrastructure." - IDC "The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments" - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence. Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management. Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage. Job Description This is a Hybrid role located in Columbia, Maryland. Data Scientist for Enhancing Support Operations Responsibilities for this role include but are not limited to: Developing strategies to identify and mitigate inefficiencies in support operations for ExaScaler and SFA systems. Automating the collection and analysis of logs to reduce support resolution times. Designing and implementing real-time health scoring systems and dashboards for quick assessment of system status. Enhancing the search functionality of the knowledge base using natural language processing (NLP) algorithms. Developing a recommendation engine to suggest relevant articles and solutions based on context. Implementing machine learning algorithms to detect duplicate issues in Jira and providing automated merge suggestions. Creating and maintaining a centralized database of available patches and developing automated notifications for relevant patches. Collaborating with support engineers, sales engineers, and other stakeholders to understand requirements and deliver effective solutions. Documenting solutions, including implementation details and user guides, and providing training to support teams. Qualifications: BS/MS in Data Science, Computer Science, Computer Engineering, or equivalent degree/experience. 4+ years of experience in data analytics, machine learning, and automation. Proficiency in programming languages such as Python, R, or Java. Experience with data processing frameworks like Hadoop, Spark, or similar. Strong knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, Scikit-learn). Familiarity with natural language processing (NLP) techniques and tools. Experience with database systems and SQL. Strong problem-solving skills and ability to work with large datasets. Excellent communication skills and ability to collaborate with cross-functional teams. Self-starter with the ability to work independently and manage multiple tasks. Knowledge of distributed systems is a plus. Familiarity with version control systems like Git. Experience with issue tracking and CI/CD tools such as JIRA, Jenkins, Gerrit, and GitHub is useful. Salary Range: $66,000.00 - $122,500.00 DDN Our team is highly motivated and focused on engineering excellence. We look for individuals who appreciate challenging themselves and thrive on curiosity. Engineers are encouraged to work across multiple areas of the company. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. Interview Process: After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 30-minute interview ("phone interview") during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews: Coding assessment in a language of your choice. Systems design: Translate high-level requirements into a scalable, fault-tolerant service. Systems hands-on: Demonstrate practical skills in a live problem-solving session. Project deep-dive: Present your past exceptional work to a small audience. Meet and greet with the wider team. Our goal is to finish the main process within one week. We don't rely on recruiters for assessments. Every application is reviewed by a member of our technical team. DataDirect Networks, Inc. is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.
Created: 2024-11-13