At a Glance
- Tasks: Drive innovative data solutions across cybersecurity platforms and develop analytical data pipelines.
- Company: Join Black Duck Software, a pioneer in application security with a collaborative culture.
- Benefits: Enjoy competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic environment with opportunities for travel and collaboration across teams.
- Why this job: Make a real impact by leveraging data to enhance security and decision-making processes.
- Qualifications: 5+ years in Data Science or related fields; strong programming skills required.
The predicted salary is between 30000 - 50000 ÂŁ per year.
Black Duck Software, Inc. helps organizations build secure, high-quality software, minimizing risks while maximizing speed and productivity. Black Duck, a recognized pioneer in application security, provides SAST, SCA, and DAST solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behaviour.
The Data Science group serves under the Black Duck Data Engineering organization as a centre of excellence in data analysis, statistical interpretation, machine learning engineering, attribution analysis and operational metric review. Our core purview is the application of historical data to drive future decision making, and to develop and maintain machine learning and analytical tools to improve service delivery and advise operational processes.
We also serve as mediators of meaning across Black Duck, and as custodians of a shared data ecosystem. This ecosystem serves to empower data consumers to explore client-operational and service-ops data in more intuitive ways, and supports their ability to share and collaborate on best practices for using this data in truthful, responsible, ethical and efficient ways.
Our Values
- Trust: Our work has no value if it is not trusted by our colleagues/customers, or if our work is not respectable. We will always rather be late than incorrect.
- Collaboration: We have a “very specific set of skills”, however we should humbly respect the subject matter experts we work with in their fields of expertise; we’re experts shuffling bits around faster/better/smarter, but they do the real work.
- Results: For our work to have value, it must speed up, augment, or replace, a current decision making process, or to demonstrate a new product/operational opportunity. While the “value” of a result may not be known for a long time, we are still outcome-driven.
- Curiosity: Exploration and Experimentation is at the heart of what we do, and we empower each other with the freedom to explore, and possibly get lost in, longer term research projects than other groups. However, even those dead ends have value when they’re written up.
- Fun: We’re in this business because we enjoy the strange and often incongruous world of data, and what that data can tell us about ourselves. Revel in the comedy of your mistakes and discoveries, and share them with abandon.
About the Role
As a Data Engineer/Scientist, you will be a custodian of our cross-functional data regime, and a driver of innovative uses of Data across our cybersecurity platforms, ranging from predictive analytics and customer behavioural analysis, through to training customised machine learning models on continuously evolving feedback streams from data and decisions that really matter to our thousands of customers that rely on our security assessments for safety, stability, and often, sleep. The role is primarily based around our Belfast R&D Site, but UK/EMEA remote or hybrid applicants will be considered. At least Quarterly travel to the Belfast R&D Site is expected, and additional travel / conference opportunities may be available depending on your impact and collaboration.
Key Responsibilities
- Developing and maintaining analytical data pipelines from a range of sources, internal and external.
- Participate in system design discussions and contribute to architectural decisions.
- Evaluating new analytical / technological opportunities for leveraging those data for security/business impact.
- Leading projects from research through to production deployment and operational handover to appropriate teams.
- Partnering with R&D and Engineering teams to develop and share best practices for data tooling, from pipelines and dashboards to ML and LLM integration.
Key Qualifications
- 5+ years of experience working in Data Science, AI/Data Engineering, Data Operations, DevOps, Business Analytics, or a related field.
- BSc Or MSc in Computer Science, Data Science, Artificial Intelligence, Math, Physics, Engineering or related field/degree.
- Experience in a relevant analytical programming language the point where you can build / deliver a project/module from scratch that can be used by others (Python is our main daily-driver, expert-level experience in Julia or Rlang could be accepted).
- Experience in Jupyter Notebook / equivalents.
- Experience in Airflow, DBT, Databricks, or equivalent stacks.
- Experience in the PyData / Spark or equivalent analytical stacks.
- Familiarity with Cybersecurity Governance, Application Security Testing, Quality Assurance or similar.
- Experience in data modelling and working with RDBMS (PostgreSQL, Oracle or MySQL) and knowledge of NoSQL databases (e.g. MongoDB).
- Experience with Machine Learning and AI systems.
- Hands-on experience with AI-assisted development tools (e.g., GitHub Copilot, Claude Code, Cursor, or similar).
- Independent project operation and cross-functional collaboration.
- Strong or Developing communication skills (in-person and remote).
Nice to have
- Familiarity with Data Mesh/Data Product concepts.
- Experience in operating in Linux Command line environments.
- Experience in Langchain or equivalent Agentic development stack.
- Experience in training custom Machine Learning models, including familiarity with evaluation criteria and metric design.
- Experience in integrating AI capabilities into software systems, including prompt engineering, API integration, and leveraging LLM-based services for automation and productivity.
- Experience in Enterprise Data Visualisation such as Power BI, Tableau, Grafana, DataBricks, Snowflake etc.
- Experience deploying ML/AI models in production environments/workloads.
- Experience in developing/working within large enterprise applications using microservices architecture, and container orchestration technologies, running on Kubernetes and/or cloud technologies (AWS, Azure or GCP).
- Experience in software architecture, systems design, interaction design (to the point where you can have constructive conversations with security / architecture leaders).
Black Duck considers all applicants for employment without regard to race, colour, religion, sex, gender preference, national origin, age, disability, or status as a Covered Veteran in accordance with federal law. In addition, Black Duck complies with applicable state and local laws prohibiting discrimination in employment in every jurisdiction in which it maintains facilities. Black Duck also provides reasonable accommodation to individuals with a disability in accordance with applicable laws.
Data Scientist/Engineer in Belfast employer: Black Duck Software, Inc.
Contact Detail:
Black Duck Software, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist/Engineer in Belfast
✨Tip Number 1
Network like a pro! Reach out to current employees at Black Duck or in the data science community. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio of projects that highlight your experience with data pipelines, machine learning, and any relevant tools. Bring this to interviews to demonstrate your hands-on expertise.
✨Tip Number 3
Be curious and ask questions during interviews! Show your enthusiasm for data exploration and how you can contribute to Black Duck's mission. This not only shows your interest but also aligns with their values.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at Black Duck.
We think you need these skills to ace Data Scientist/Engineer in Belfast
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist/Engineer role. Highlight relevant experience and skills that match the job description, especially in data analysis, machine learning, and programming languages like Python.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data and how your background aligns with our values at Black Duck. Don’t forget to mention any specific projects or experiences that showcase your skills.
Showcase Your Projects: If you've worked on any interesting data projects, make sure to include them in your application. Whether it's a personal project or something from work, demonstrating your hands-on experience can really set you apart.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at Black Duck Software, Inc.
✨Know Your Data Tools
Make sure you’re well-versed in the analytical programming languages and tools mentioned in the job description, especially Python. Brush up on your experience with Jupyter Notebook, Airflow, and any relevant data stacks like PyData or Spark. Being able to discuss specific projects where you've used these tools will show your hands-on experience.
✨Showcase Your Curiosity
Black Duck values curiosity and exploration, so be prepared to discuss any long-term research projects you've undertaken. Share what you learned from any dead ends or unexpected results. This not only demonstrates your passion for data but also aligns with their value of experimentation.
✨Collaboration is Key
Highlight your experience working cross-functionally with R&D and engineering teams. Be ready to discuss how you’ve partnered with others to develop best practices for data tooling. This shows that you understand the importance of collaboration in achieving results, which is a core value at Black Duck.
✨Prepare for Technical Questions
Expect technical questions related to machine learning, data modelling, and cybersecurity concepts. Brush up on your knowledge of NoSQL databases and AI systems. Practising common interview questions in these areas can help you articulate your expertise clearly during the interview.