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- Tasks: Join us as a Solutions Analyst, training machine learning classifiers with patent data and collaborating with clients.
- Company: LexisNexis Intellectual Property transforms patent data into actionable insights for strategic decision-making.
- Benefits: Enjoy remote work flexibility, a collaborative environment, and opportunities for professional growth.
- Why this job: Be part of an innovative team, tackling real-world challenges in technology and intellectual property.
- Qualifications: A STEM degree is required; no prior experience in machine learning or data analysis needed.
- Other info: We value diversity and are committed to an inclusive hiring process.
The predicted salary is between 36000 - 60000 £ per year.
Location: HOME BASED, London, City of, United Kingdom
Contract Type: Regular
Schedule: 35
Job ID: R93085
About the Business
LexisNexis Intellectual Property is committed to extracting value from patent data to enable companies and investors to make informed strategic decisions. We recognise the importance of intellectual property as a growing mainstream asset class and the role of patents in providing a window into who is leading technology innovation, where, and at what pace.
About the Team
We are committed to delivering high-quality solutions tailored to the specific needs of our customers. By harnessing the latest advances in machine learning combined with expert analysis, LexisNexis Intellectual Property is transforming how actionable insights are extracted from patent data. Information can now be accessed with efficiency, accuracy, and at a speed that traditional methods simply cannot achieve.
About the role
As a Solutions Analyst, you will be a key part of the Solutions and Consulting Team, responsible for designing and deploying custom classifiers across our growing customer base. You will collaborate closely with internal teams and customers and play a key part in all aspects of the delivery process – from pre-sales support through to project delivery. The primary responsibility of this role will be the training of machine learning classifiers using patent data across a variety of technologies and industries. This supervised learning process is conducted using the proprietary ‘Cipher’ platform - no prior experience with machine learning techniques is required.
Responsibilities
- Training supervised machine learning classifiers with curated patent data to enable automated patent tagging against specific technologies.
- Conducting desk-based research into various technologies and products.
- Working with customers to understand their specific needs and challenges.
- Defining and structuring project scopes to develop client classifier taxonomies.
- Participating in customer meetings for scoping and data review – with a lead analyst, gaining valuable exposure to client interactions.
This role is ideal for inquisitive individuals with a strong interest in both established and emerging technologies. You can expect a collaborative environment with opportunities to problem-solve and contribute to qualitative and quantitative analysis. As the role progresses, you will be:
- Working with customers to understand their specific needs and challenges.
- Ad-hoc data analysis and presentation when required to meet a customer goal.
- Leading customer meetings for scoping, data review, and data presentation purposes.
- Opportunity to also contribute to our Solutions & Consulting opportunities using tools from across our product suite.
Requirements:
- No previous experience in machine learning, programming, or data analysis platforms is required.
- A bachelor's degree in a STEM field.
- Knowledge of the Intellectual Property field is desirable but not required.
- A keen interest in innovation and technology trends.
- Strong collaboration skills and the ability to work in a multi-disciplinary team.
- An analytical mindset and enthusiasm for data-driven storytelling.
- Strong communication skills with the ability to participate in customer-facing activities.
- Most importantly, you must be a motivated self-starter who can effectively prioritise work to ensure timely project delivery.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, colour, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. EEO Know Your Rights.
Solutions Analyst employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Solutions Analyst
✨Tip Number 1
Familiarise yourself with the basics of machine learning and how it applies to patent data. Even though prior experience isn't required, having a foundational understanding will help you engage in conversations with the team and demonstrate your enthusiasm for the role.
✨Tip Number 2
Research LexisNexis Intellectual Property and their Cipher platform. Understanding their products and services will allow you to speak knowledgeably about how you can contribute to their goals during interviews.
✨Tip Number 3
Prepare to discuss your analytical mindset and problem-solving skills. Think of examples from your academic or professional experiences where you've successfully tackled challenges, as this will resonate well with the collaborative nature of the team.
✨Tip Number 4
Showcase your communication skills by practicing how you would explain complex concepts simply. This is crucial for customer-facing activities, so being able to articulate your thoughts clearly will set you apart from other candidates.
We think you need these skills to ace Solutions Analyst
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Solutions Analyst. Familiarise yourself with the key tasks such as training machine learning classifiers and collaborating with customers.
Tailor Your CV: Highlight your educational background in a STEM field and any relevant skills or experiences that align with the job description. Emphasise your analytical mindset and interest in technology trends.
Craft a Compelling Cover Letter: Use your cover letter to express your enthusiasm for the role and the company. Mention specific aspects of LexisNexis Intellectual Property that resonate with you and how your skills can contribute to their mission.
Showcase Collaboration Skills: Since the role requires strong collaboration skills, provide examples in your application of how you've successfully worked in teams or engaged with clients in previous roles or projects.
How to prepare for a job interview at LexisNexis Risk Solutions
✨Understand the Role
Make sure you have a clear understanding of what a Solutions Analyst does, especially in relation to training machine learning classifiers. Familiarise yourself with the responsibilities outlined in the job description and think about how your skills align with them.
✨Show Your Interest in Technology
Since the role requires a keen interest in innovation and technology trends, be prepared to discuss recent advancements in these areas. This could include mentioning specific technologies or trends that excite you and how they relate to the work LexisNexis is doing.
✨Prepare for Customer Interaction Scenarios
As the role involves customer meetings and understanding their needs, think of examples from your past experiences where you've successfully collaborated with others or solved problems. Be ready to demonstrate your strong communication skills and ability to engage with clients.
✨Highlight Your Analytical Mindset
The position requires an analytical mindset and enthusiasm for data-driven storytelling. Prepare to discuss any relevant experiences where you've used data to make decisions or tell a story, even if it's from academic projects or personal interests.
