At a Glance
- Tasks: Analyse data and develop innovative solutions to advance healthcare automation.
- Company: Join ATS Corporation's Innovation Center, a hub for cutting-edge R&D.
- Benefits: Competitive salary, performance bonuses, generous vacation, and health benefits.
- Other info: Collaborative team culture with opportunities for continuous learning and global mobility.
- Why this job: Make a real impact in healthcare while growing your career in a dynamic environment.
- Qualifications: Post-secondary degree in a quantitative field and strong experience with Databricks.
The predicted salary is between 70000 - 90000 £ per year.
Benefits:
- Compensation: $88,000 - $121,000
- Annual Performance-Based Incentive Bonus 5%
- RRSP match
- Stock purchase plan
- Starting 3 weeks of vacation
- Benefits package (health and dental) + $600 health spending account
- Half-Day Fridays
- Continuous learning and career growth with global mobility opportunities.
- A chance to contribute to something bigger - advancing the future of healthcare through automation.
Qualifications:
- Education: A post-secondary engineering degree, diploma or equivalent in a quantitative field (Computer Science, Information system, Mathematics, Statistics, Machine Learning, Artificial Intelligence, Engineering). A Master’s degree is considered beneficial.
- Experience:
- Strong experience with the deployment, configuration, and operationalization of Databricks environments, including workspace architecture, cluster management, CI/CD integration, security, governance, and enterprise-scale administration.
- Experienced in building and managing modern data pipelines and lakehouse architectures using Delta Lake, Delta Live Tables, Structured Streaming, Workflows, medallion architectures (Bronze/Silver/Gold), and real-time/batch ingestion frameworks.
- Deep understanding of Databricks ecosystem components including Unity Catalog, data lineage, RBAC, monitoring/observability, cost optimization, ML/AI enablement, model serving, and secure enterprise data collaboration through Clean Rooms.
- Proven experience integrating Databricks with enterprise cloud and industrial data ecosystems, including Kafka, SQL databases, APIs, IoT/OT platforms, and cloud environments such as Azure, AWS, and GCP.
- Strong understanding of scalable data engineering, governance, multi-tenant architectures, and enterprise data platform strategies supporting analytics, AI, and operational intelligence initiatives.
- Proficiency in programming languages like Python, R, or Java.
- Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with databases (SQL, Influx).
- Knowledge of data warehousing and ETL processes.
- Familiarity with tools like Hadoop, Spark, or Kafka.
- Experience with cloud services such as AWS, Google Cloud, or Azure.
- Understanding of software engineering principles and best practices.
- Experience with version control systems (e.g., Git).
- Ability to design and implement efficient algorithms and solutions.
- Demonstrated experience in deploying machine learning models to production.
- Experience with data visualization tools and techniques.
- Strong analytical and communication skills.
- Ability to work collaboratively in a team environment.
- Ability to communicate effectively, both orally and in writing.
- A self-starter with the ability to work as part of a team in a fast-paced environment with minimal supervision.
- In addition, the following is considered not necessary but beneficial:
- Experience with Agile development practices.
- Understanding of automation mechanical, electrical and control systems.
- Understanding of machine operation, maintenance, service and troubleshooting.
- Understanding of Machine Vision systems and solutions.
- Understanding of PLCs and PLC communication.
- Exposure and understanding of business intelligence.
Health, Safety, and Environmental:
- All employees have the responsibility to work in a safe manner and report any health, safety or environmental concern to their manager or supervisor in a timely manner.
- Work in compliance with divisional health, safety and environmental procedures.
- Refrain from removing or altering safety devices or guarding unless hazardous energies are controlled through lockout-tagout methods.
- Report any unsafe conditions or unsafe acts.
- Report defect in any equipment or protective device.
- Ensure that the required protective equipment is used for the assigned tasks.
- Attend all required health, safety and environmental training.
- Report any accidents/incidents to supervisor.
- Assist in investigating accidents/incidents.
- Refrain from engaging in any prank, contest, feat of strength, unnecessary running or rough and boisterous conduct.
Join our Innovation Center at ATS Corporation - a place to create differentiators with the future in mind. Our Innovation Center is focused on R&D; advancing existing technologies, filling gaps in existing automation products, technologies and processes to give ATS a competitive advantage.
Data Scientist in Cambridge employer: ATS Corporation
At ATS Corporation, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Data Scientist in our Innovation Center, you'll enjoy competitive compensation, generous vacation time, and a robust benefits package, all while contributing to the advancement of healthcare through cutting-edge automation technologies. With continuous learning opportunities and global mobility, we empower our employees to grow their careers and make a meaningful impact in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks and data pipelines. It’s a great way to demonstrate what you can do beyond the application.
✨Tip Number 3
Prepare for interviews by practising common data science questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Data Scientist in Cambridge
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your relevant experience with Databricks, data pipelines, and any programming languages you’re proficient in. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about advancing healthcare through automation. Share specific examples of your past work that relate to the job description. Let us know why you’d be a great fit!
Showcase Your Projects:If you’ve worked on any cool projects, especially those involving machine learning or data engineering, make sure to mention them. We love seeing practical applications of your skills, so don’t hold back on sharing your achievements!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at ATS Corporation
✨Know Your Tech Inside Out
Make sure you’re well-versed in the Databricks ecosystem and its components. Brush up on your knowledge of Delta Lake, CI/CD integration, and data pipelines. Being able to discuss these topics confidently will show that you’re not just familiar with the tools but can also apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use examples that highlight your analytical skills and ability to design efficient algorithms. This will demonstrate your capability to contribute to the team’s success in a fast-paced environment.
✨Communicate Clearly and Effectively
Practice articulating your thoughts clearly, especially when discussing complex technical concepts. Remember, communication is key in collaborative environments. Be ready to explain your past projects and decisions in a way that’s easy for anyone to understand, regardless of their technical background.
✨Emphasise Continuous Learning
Given the focus on career growth and continuous learning, be prepared to discuss how you stay updated with industry trends and technologies. Mention any relevant courses, certifications, or personal projects that showcase your commitment to professional development and innovation in data science.
