Lead Data Specialist, ML Data Ops

Amazon
London
4 days ago
Create job alert

Whenever a customer visits Amazon and types in a query or browses through product categories, Amazon Search services go to work. The Search Ops team helps Search services in providing a better customer search experience by delivering quality data annotation to help improve AI/ML models driving these services.

Our vision is to create business value by delivering high quality data at scale. We look to provide easy and scalable labeling solutions to support search that are high quality, cost-efficient, and secure. Our vision is to enable improvement in the search experience for our customers, by accurately determining labels for products targeted by the search queries received. We collaborate closely with several machine learning (ML) applied science teams that develop and test ML models to improve the quality of semantic matching, ranking, computer vision, image processing, and augmented reality.

To support our vision, we need exceptionally talented, bright, and driven people. Duties will include ensuring that standards for productivity and quality assurance are met by your team, taking part in planning, organizing, and directing the work of subordinates or others, outlining procedures and instructions on work received, making time estimates on new jobs received, ensuring high utilization of the team, and mentoring and training new/existing team members. If you have what it takes then this is your chance to work hard, have fun, and make history.

Key job responsibilities

As a Lead Data Specialist, ML Data Ops, you will be responsible for meeting operational and business goals overlooking about 30-40 associates, having expertise in one or more processes/functions. You will also be a driving initiative across sites for process improvements, SoP and guidelines formulation, diving deep to provide data insights as and when required. Your key responsibilities will include (but not limited to) the below:

  1. Data Analysis:Conduct in-depth analysis of data to identify patterns, problems, root causes, and potential solutions, leveraging analytical tools and techniques.
  2. Stakeholder Collaboration:Collaborate effectively with relevant stakeholders to align data analysis efforts with business goals, ensuring insights drive decision-making and strategic initiatives.
  3. Escalation Management:Manage escalations by analyzing data, identifying trends and gaps, and reporting key metrics to facilitate informed decision-making and resolution.
  4. Process Improvement:Review standard operating procedures (SOPs), processes, and tools to proactively identify areas for improvement, striving to enhance quality metrics and operational efficiency.
  5. Continuous Improvement:Drive continuous improvement initiatives, actively contributing to the Correction of Error (COE) process by documenting data curation and annotation issues and suggesting improvements.
  6. Leadership Support:Participate in business reviews with mid-level and senior leadership, providing valuable insights and support to drive strategic objectives.
  7. Process Onboarding:Participate in the onboarding of new processes or experiments, ensuring comprehensive documentation and smooth integration into existing workflows.
  8. Launch Plan Development:Develop robust launch plans for new team members and oversee progress tracking through the administration of launch plans, ensuring seamless integration and productivity.
  9. Training and Coaching:Coach new hires on process tasks and provide feedback to the training team for the customization of training modules, facilitating skill development and performance improvement.
  10. Backup Support:Serve as a backup for the identified manager and provide support to the respective team in various aspects, ensuring continuity of operations and effective team functioning.
  11. Quality Assurance:Perform quality checks on annotated data with a high level of precision, adhering to annotation guidelines and maintaining data integrity and accuracy.
  12. Sensitive Data Handling:Demonstrate willingness to work with sensitive data, including adult content, religious, and other sensitive issues, adhering to privacy and confidentiality protocols.

BASIC QUALIFICATIONS

- A Bachelor’s Degree and relevant experience of 2+ years as a subject matter expert or similar.
- Intermediate knowledge and hands-on experience with MS Excel.
- Strong written & spoken communication skills.
- Strong attention to detail and the ability to successfully manage multiple competing priorities simultaneously.

PREFERRED QUALIFICATIONS

- Knowledge of SQL, Python scripting, and Machine learning.
- Understanding of quality-related concepts & tools such as 5Ys, 7 QC, F.M.E.A.
- Experience in e-commerce and online retail.
- Certified Six Sigma Green Belt.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visitthis linkfor more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Posted:December 16, 2024 (Updated about 7 hours ago)

Posted:January 2, 2025 (Updated about 7 hours ago)

Posted:February 17, 2025 (Updated about 8 hours ago)

Posted:June 7, 2024 (Updated about 9 hours ago)

Posted:January 7, 2025 (Updated about 9 hours ago)

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analyst - Market Research Consultancy

Data Analyst - Market Research Consultancy

Data Acquisition Lead

Senior Data Analyst

Test Specialist

Course Leader MSc Business and Data Analytics - London

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

Career Paths in Machine Learning: From Entry-Level Roles to Leadership and Beyond

Machine learning has rapidly transformed from an academic pursuit to a cornerstone of modern technology, fueling innovations in healthcare, finance, retail, cybersecurity, and virtually every industry imaginable. From predictive analytics and computer vision to deep learning models that power personalisation algorithms, machine learning (ML) is reshaping business strategies and creating new economic opportunities. As demand for ML expertise continues to outstrip supply, the UK has become a vibrant hub for machine learning research, entrepreneurship, and corporate adoption. Whether you’re just starting out or have experience in data science, software development, or adjacent fields, there has never been a better time to pursue a career in machine learning. In this article, we will explore: The growing importance of machine learning in the UK Entry-level roles that can kick-start your ML career The skills and qualifications you’ll need to succeed Mid-level and advanced positions, including leadership tracks Tips for job seekers on www.machinelearningjobs.co.uk By the end, you’ll have a clear view of how to build, grow, and lead in one of the most exciting fields in modern technology.