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The "Data Scientist" is the Big Data specialist in companies, responsible for structuring information and optimizing the security of stored data, regardless of their volume. Their mission: carefully categorize data to avoid risks of IT system failure. They thus seek to detect new vulnerabilities potentially exploitable by hackers and their impact on company activities. Ultimately, they ensure to propose effective protection solutions. This expert in massive data management and analysis is simultaneously a specialist in numbers, statistics, and computer programs: they extract value from data to support the company in making strategic or operational decisions. The "Data Scientist" collaborates transversally with various profiles: computer scientists, statisticians, data analysts, data miners, marketing and web marketing experts...

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Job VacancyAI/ML Data Engineer

LA International Computer Consultants Ltd
Published on

6 months
Swindon, United Kingdom
Our government client is looking for candidates who have at least one production AI/ML implementation, recent experience with AWS data services, Terraform, CI/CD, Python, and SQL. Candidates should have more than five years of overall experience and meet the other requirements outlined in the attached JD. Inside IR35 Monthly travel to Swindon, mostly remote Initial 6 months + extensions Job Purpose: The BI Engineer will be responsible for the requirements analysis and design of solutions for data platform, ETL, integration and analysis solutions. Our toolset includes AWS hosted databases (postgres, S3 based data lake, MySQL, Athena), integration services (AWS API gateway, lambda functions), ETL services (AWS Glue, Step functions, AWS Batch), infrastructure a management tool such as Terraform and extensive use of SQLs and python. Key Responsibilities and Accountabilities: The BI Engineer will be a hands-on data developer to develop and construct complete solution designs to complex application requirements across platforms and data sources: 1. Infrastructure Management: a. Set up and manage data infrastructure, including clusters, servers, and cloud-based resources using Terraform. b. Monitor and optimize system performance, troubleshoot issues, and ensure system availability. 2. Data Architecture and Design: a. Design and implement scalable and efficient data pipelines, databases, and data warehouses. b. Collaborate with data visualization and analysts' teams to understand data requirements and translate them into technical specifications. 3. Data Processing: a. Develop and maintain ETL (Extract, Transform, Load) processes for ingesting data from various sources into the data infrastructure. b. Optimize data processing and storage for performance and cost-effectiveness. 4. AI: a. Develop and deploy AI/ML models into production environments. b. Build scalable inference pipelines and AI APIs. c. Implement MLOps workflows for model versioning, monitoring, and retraining. d. Collaborate with data scientists to productionize machine learning solutions. e. Evaluate and optimize AI model performance and operational efficiency. 5. Database Management: a. Manage and maintain databases, ensuring data integrity, security, and availability. b. Implement database schema changes and optimizations as needed. 6. Collaboration: a. Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to meet data requirements. b. Communicate effectively with stakeholders to gather requirements and provide updates on data engineering projects. To Achieve this, you will have the following skills: * Comfortable working in an Agile rapidly changing environment * You will be an accomplished developer and BI Engineer, with excellent python skills. * Experience with the infrastructure deployment tool such as terraform, CDK or cloud formation. * Experience developing API based data integration. * Excellent analytic skills associated with working on structured and unstructured datasets. * Excellent SQL experience on various platforms (SQL, PostgresSQL, PL/SQL etc) * Experience of several of MySQL, Oracle, SQL, Postgres, RDS, Aurora, Athena or other similar large scale database technologies. * Experience working with AI framework such as LangChain / LlamaIndex * Experience with Vector databases (Pinecone, Weaviate, FAISS) This is an outline description of the key responsibilities and accountabilities involved in the job. This is not an exhaustive list and the post-holder might be expected to undertake any other duties across the wider directorate, commensurate with the Band and level of responsibility of this post, for which the post holder has the necessary experience and/or training. LA International is an award-winning partner of choice for many of the world's most influential companies and government organisations. Holding Enhanced Government Security Accreditation, we are recognised as the European market leader in the delivery of Security Cleared talent to organisations that demand the very highest levels of security, compliance and assurance. A multiple award-winning organisation, having secured the prestigious Queens Award for Enterprise: International Trade over consecutive years. We are committed to fostering an inclusive, equitable and accessible workplace where everyone feels valued and supported. We welcome applications from all individuals, regardless of background or identity, and we encourage candidates who may not meet every listed requirement to still apply. If you require any adjustments or support during the recruitment process, please let us know and we will work with you to ensure a fair and accessible experience. Please Note: If a high volume of applications is received, only candidates shortlisted will be contacted.
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Permanent

Job VacancyLead Data Engineer

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Published on
Apache Kafka
Apache Spark
Big Data

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Frequently asked questions about working as a Data Scientist

What is the role of a Data Scientist

In the Big Data era, the Data Scientist is somewhat the evolution of the Data Analyst. He/she is a specialist in analyzing and exploiting data within a company. His/her role is to give meaning to this data, in order to extract value from it, to enable the company to make strategic and/or operational decisions. It is one of the high-responsibility positions in a company.

How much does a Data Scientist charge

The average daily rate of a freelance data scientist is around £450/day. It can vary depending on years of experience and the professional's geographical location. The salary of a junior data analyst is £35K. The salary of an experienced data scientist ranges from £50K to £60K.

What is the definition of a Data Scientist

The Data Scientist is an essential element of the company, given that they are responsible for analyzing massive data called Big Data. They manage the collection, storage, analysis and use of millions of data points collected through different channels. This data is used to analyze company performance, and to anticipate consumer behaviors or new trends. It's both an exciting and promising field. It generates new challenges and allows professionals to continuously gain skills. The Data Scientist has solid knowledge in marketing. This professional is highly sought after by companies that constantly seek to improve their performance and remain competitive. After completing their analysis, the Data Scientist will then write a report explaining their conclusions to management or their client.

What type of mission can a Data Scientist handle

The Data Scientist's main mission is to "predict the future". The significant amount of data that companies now generate can be very useful if used properly. The data scientist can then ensure the strategic development of the company, as well as its digital transformation. To achieve this, they must decipher opaque masses of data to give them meaning. Their role is therefore to transform data into actionable information. They can offer their clients IT management solutions to meet specific needs. Creating algorithms will allow them to anticipate future behaviors and needs in order to guide important decisions. It is this form of creativity that distinguishes them from the Data Analyst. Thanks to their expertise, the Data Scientist must be able to present innovative and relevant proposals to their clients, implement and deploy machine learning models, and finally communicate their conclusions to the relevant departments. They can work on short or medium-term projects.

What are the main skills of a Data Scientist

The Data Scientist must master many skills to effectively carry out their duties. We can mention a few: • Being able to efficiently analyze statistical data and model it • Having good knowledge of programming tools and computer language • Mastering data visualization techniques • Having strong affinities for marketing • Having business sense and good communication skills • Being rigorous, organized, with the ability to make proposals • Being able to maintain data confidentiality • Knowing how to work in a team, under pressure and manage stress • Conducting IT monitoring

What is the ideal profile for a Data Scientist

Many schools are beginning to offer degrees in mathematics and applications with specialization in statistics, Big Data engineering, or massive data analysis. There are also other training programs that provide access to the Data Scientist profession, particularly in higher education schools for computer science, statistics, or engineering schools. However, it will still be necessary to demonstrate 4 to 5 years of experience in data analysis or in a datacenter environment.

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