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- Career Change
Data Science Placement Programme5 days ago£25000–£45000 yearlyFull-timeBricket WoodAre you looking to kick-start a new career as a Data Scientist? We are recruiting for companies who are looking to employ our Data Science Traineeship graduates to keep up with their growth. The best part is you will not need any previous experience as full training will be provided. You will also have the reassurance of a job guarantee (£25K-£45K) within 20 miles of your location upon completion. Whether you are working full time, part-time or unemployed, this package has the flexibility to be completed at a pace that suits you. The traineeship is completed in 4 easy steps, you can be placed into your first role in as little as 6-12 months: Step 1 - Full Data Science Career Training You will begin your data science journey by studying a selection of industry-recognized courses that will take you from beginner level all the way through to being qualified to work in a junior Data Scientist role. Through the interactive courses, you will gain knowledge in Python, R, Machine Learning, AI, and much more. You will also complete mini projects to gain practical experience and test your skills while you study. Step 2 - CompTIA Data+ CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. It teaches Data Mining, Visualization, Data Governance & Data Analytics. In any industry, gaining official certifications is very important in the recruitment process. Therefore, this globally recognized certification will enhance your CV and make you stand out from the crowd. Step 3 - Official Exam The CompTIA Data+ exam will certify that you have knowledge and skills required to transform business requirements in support of data-driven decisions through mining and manipulating data, applying basic statistical methods, and analysing complex datasets while adhering to governance and quality standards. The exam is 90 minutes long and can be sat either in your local testing centre or online. Step 4 - Practical Projects Now that you have completed your theory training and official exams, you will be assigned 2 practical projects by your tutor. The projects are the most important part of the traineeship as it will showcase to employers that you have skills required to work in a data science role. The projects will use real world scenarios where you be utilising all of the skill that you have learned. Whilst you are progressing through the projects, you will have the ongoing support from your personal tutor. Once both projects have been completed and given the final sign off, you will have completed the traineeship and will be ready to move onto the recruitment stage. Your Data Science Role Once you have completed all of the mandatory training, which includes the online courses, practical projects and building your own portfolio, we will place you into a Data Scientist role, where you will be guaranteed a starting salary of £25K-£45K. We have partnered with a number of large organisations strategically located throughout the UK, providing a nationwide reach of jobs for our candidates. We guarantee you will be offered a job upon completion, or we will refund you 100% of your course fees back. We have a proven track record of placing 1000+ candidates into new roles each year. Check out our website for our latest success stories. Read through the information? Passionate about starting a career in data science? Apply now and one of our friendly advisors will be in touch.
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Interviews tomorrowData Analyst20 hours ago£55000–£60000 yearlyFull-timeBorehamwoodSummary: Are you passionate about uncovering insights hidden within data? We're looking for a Data Analyst to join our team and play a key role in driving data-driven decisions. You'll be responsible for collecting, processing, and analyzing complex datasets to identify trends, patterns, and opportunities that will help our organization achieve its strategic goals. Your work will directly influence business outcomes by providing actionable intelligence to stakeholders across the company. Responsibilities: Collect data from various sources, including databases, APIs, and other systems. Clean and prepare data for analysis, ensuring accuracy and consistency. Analyze data using statistical methods and tools (e.g., SQL, Excel, Python, R) to identify key trends, patterns, and anomalies. Develop and maintain reports, dashboards, and data visualizations to communicate findings to technical and non-technical audiences. Collaborate with cross-functional teams (e.g., marketing, sales, operations) to understand their data needs and provide analytical support. Identify opportunities to improve data collection, processing, and analysis methodologies. Document data analysis processes and findings to ensure reproducibility and knowledge sharing. Stay up-to-date with the latest trends and technologies in data analysis. Qualifications: Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science) or equivalent experience. Proven experience as a Data Analyst or in a similar role. Strong proficiency in SQL for data extraction and manipulation. Excellent skills in Excel for data analysis and reporting. Experience with data visualization tools (e.g., Tableau, Power BI) is highly desirable. Familiarity with programming languages such as Python or R for statistical analysis is a plus. Solid understanding of statistical concepts and methods. Strong analytical and problem-solving skills with a keen attention to detail. Excellent communication and presentation skills, with the ability to convey complex information clearly and concisely. Ability to work independently and collaboratively in a fast-paced environment. Job Description: Computer analysts and scientists research, design, develop, and optimize computer systems, algorithms, and software. They analyze computing needs, explore emerging technologies like AI, machine learning, and big data, and develop innovative solutions to complex computing problems. They may also work in theoretical research or applied computer science across various industries. Job Description: Data architects design and manage an organization’s data infrastructure. They create data models, define data standards, and ensure data systems are structured to support business processes, analytics, and decision-making. They establish policies for data integration, storage, and security, often collaborating with engineers and analysts. Data engineers build and maintain data pipelines and architectures that allow organizations to collect, process, and analyze large sets of data. They work on database management, ETL (Extract, Transform, Load) processes, data warehouses, and big data platforms, ensuring data is reliable, accessible, and efficiently processed for analysts and business use. IT systems architects design and implement the overall structure of IT systems within an organization. They ensure systems are scalable, secure, and aligned with business goals. They create technical blueprints, integrate hardware and software components, and evaluate new technologies to optimize IT operations. IT business analysts act as a bridge between business needs and IT solutions. They gather and analyze business requirements, assess existing systems, and recommend IT solutions that improve efficiency and meet organizational objectives. They also support testing, documentation, and change management during system implementations. IT solutions architects and designers focus on creating technical solutions tailored to specific business needs. They design software, applications, or system integrations, ensuring compatibility, scalability, and compliance. Their work involves selecting technologies, defining frameworks, and guiding development teams through solution implementation. This category covers IT specialists whose roles combine aspects of business analysis, architecture, and systems design but don’t fit neatly into standard classifications. They may work on hybrid projects, such as digital transformation, enterprise integration, or custom IT strategy, often requiring a mix of technical, analytical, and business expertise.
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