Lead Operator and Data Analyst Assistant

ZipRecruiter
London
9 months ago
Applications closed

Related Jobs

View all jobs

SharePoint M365 Data Analyst

Lead Data Architect | Snowflake & AWS | £130k | Roadmap to Head of Engineering

Lead Data Scientist

Lead Data Engineer

Lead AWS Data Engineer

Lead Data Engineer

Job Description

Lead Operator- London - Earn up to £16/h - Apply Now!

At Job&Talent, we are seeking an experienced and dynamic Lead Operator to manage a diverse team of 6 drivers and 7 decay hunters/investigators/cyclists. In this role, you will be responsible for ensuring efficient team performance, coordinating shift schedules, and ensuring uptime targets are consistently met. You will also have a strategic focus on understanding the market impact of tasks and driving operational excellence across the team.

Shift Patterns:

Tuesday to Saturday - 8am-5pm

Pay Rates:

£16/h

As a Lead Operator, you will need to have:

  1. Proven experience in operations management, preferably in a similar leadership role.
  2. Strong leadership skills with experience managing teams and driving performance.
  3. Ability to develop and manage shift schedules while ensuring operational needs are met.
  4. Strong problem-solving and decision-making abilities.
  5. Understanding of market dynamics and how operational tasks impact broader business goals.
  6. Excellent communication skills and the ability to work effectively with cross-functional teams.
  7. A flexible, adaptable approach to working hours and tasks.
  8. Ability to handle high-pressure situations and meet operational targets.

Role of a Lead Operator and Data Analyst Assistant:

  1. Team Management:Supervise, lead, and support a team of 6 drivers and 7 decay hunters/investigators, ensuring tasks are executed efficiently and safely.
  2. Shift Planning:Develop and manage shift schedules, ensuring optimal coverage and resource allocation while providing flexibility to accommodate team needs.
  3. Performance Management:Monitor individual and team performance, providing feedback, guidance, and support to meet operational goals. Conduct performance reviews and facilitate training and development to improve skills and productivity.
  4. Uptime Management:Ensure uptime targets are met consistently, working closely with the team to resolve any issues that may cause delays or disruptions.
  5. Market Impact Analysis:Understand the impact of team tasks on the broader market, ensuring operations align with business objectives and market demands.
  6. Problem-Solving:Proactively address and resolve operational challenges, making adjustments as needed to maintain smooth operations.
  7. Collaboration:Work closely with other departments and stakeholders to ensure the smooth flow of operations and communicate any potential disruptions or improvements.
  8. Reporting:Regularly report team performance, uptime, and market impact to upper management, highlighting any key issues or opportunities for improvement.

Benefits of working with us as a Lead Operator and Data Analyst Assistant:

  1. Opportunity to contribute to a startup's growth.
  2. Work alongside a vibrant and motivated team.
  3. 40 hours per week with potential for overtime paid at regular rates.
  4. 28 days of holidays.
  5. Opportunities for professional development and advancement.
  6. Weekly compensation.
  7. Pension Scheme.

Location:London

Duration:Ongoing

This is an amazing opportunity if you are looking for Lead Operator jobs in London. Sign your contract with Job&Talent for some great working benefits and professional stability.

If you are interested in the above role please click apply and one of our team members will get in touch with you shortly! If you are looking to contact our onsite team, please visit the site locator on our website. Job&Talent do NOT charge any fees for our services. Job&Talent acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.