Do you want to impact a highly-skilled team that uses cutting edge techniques in Natural Language Processing and Algorithmic Trading? We are looking for an NLP Researcher that will help us greatly improve the text-processing behind our models.
At Alipes Capital, we have been the market leader in automating the financial markets since we started back in 2008, shaping a fully automatic natural language processing system for reading and interpreting financial news.
Your work
Your work will support turning massive data sets of unstructured financial information into structured datasets and mathematical models that accurately predict movements in the equity markets. In doing so, you will:
• Redesign and introduce new text-processing techniques to extract additional and more accurate entities from the text-sources that underlie our trading algorithms
• Maintain and curate new and existing text data sources for our analyses
• Automate monitoring and benchmarking of the trading strategies
• You will enjoy a wide degree of autonomy and responsibility to optimize our machine-learning pipelines, from data-ingestion to live-model performance. There is no red tape, no sales people to consult and there is ample room for creativity.
The team
All of this will happen in an informal atmosphere where technical discussions are valued and you are encouraged to take ownership of, and pride in, your work. You will impact the direction of the team, prioritize your work and choose the tools that get the job done. We are a tight-knit modeling team with fourteen passionate quantitative researchers covering six nationalities – eleven PhD’s and three MSc’s- with expertise in statistical analysis, mathematical modeling and machine learning (seven of us working directly on the text-based equity models).
We enjoy collaboration, lending a helping hand and discussing the business cases built upon our data-sets. You will be working alongside a team of software developers and a team of traders who implement and conceive the trading models with us. All team members write code and are not afraid to discuss technical details.
Need to have
• Skilled in extracting signals from texts using embeddings to enhance prediction model
• Proficient in entity-extraction from text, e.g. using modern Transformer-based Large-Language Models
• Solid understanding of machine learning techniques and their practical applications
• Aptitude for programming in a numerical scripting language (we primarily use Python)
• A meticulous and detail-oriented mind
Nice to have
• Experience using RAGs (Retrieval-Augmentation-Generation)
• Working with financial/trading data
• Experience with C#, C/C++ or Java
• Familiarity with software engineering (version control, unit testing, object oriented-design)
• Degree in Computer Science / Engineering
What we can offer you
• Flat hierarchy and high levels of trust and autonomy
• Exciting problems to solve
• Collaborative team made up of really smart and curious people
• Nice office in Nordhavn with an onsite work model
• Pension, Health Insurance and 30 days of vacation
Practicalities
To apply, please send us your CV and a cover letter telling us why you think this role is a great fit for you. In your cover letter, if applicable, please describe a project where you extracted structured or unstructured information from text - including the techniques, tools, models used and how those extractions informed further decisions/predictions. If you're selected for an interview, we will be very interested in discussing technical details with you about this project!
Should your profile look like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.
If you have questions about the role that you would like clarified before applying, you're welcome to send an email to quant_jobs@alipescapital.com. Please note that applications should not be sent to the email address but rather via the job link.
This job is based in Copenhagen, Denmark and we unfortunately cannot consider remote candidates.
At Alipes Capital, we have been the market leader in automating the financial markets since we started back in 2008, shaping a fully automatic natural language processing system for reading and interpreting financial news.
Your work
Your work will support turning massive data sets of unstructured financial information into structured datasets and mathematical models that accurately predict movements in the equity markets. In doing so, you will:
• Redesign and introduce new text-processing techniques to extract additional and more accurate entities from the text-sources that underlie our trading algorithms
• Maintain and curate new and existing text data sources for our analyses
• Automate monitoring and benchmarking of the trading strategies
• You will enjoy a wide degree of autonomy and responsibility to optimize our machine-learning pipelines, from data-ingestion to live-model performance. There is no red tape, no sales people to consult and there is ample room for creativity.
The team
All of this will happen in an informal atmosphere where technical discussions are valued and you are encouraged to take ownership of, and pride in, your work. You will impact the direction of the team, prioritize your work and choose the tools that get the job done. We are a tight-knit modeling team with fourteen passionate quantitative researchers covering six nationalities – eleven PhD’s and three MSc’s- with expertise in statistical analysis, mathematical modeling and machine learning (seven of us working directly on the text-based equity models).
We enjoy collaboration, lending a helping hand and discussing the business cases built upon our data-sets. You will be working alongside a team of software developers and a team of traders who implement and conceive the trading models with us. All team members write code and are not afraid to discuss technical details.
Need to have
• Skilled in extracting signals from texts using embeddings to enhance prediction model
• Proficient in entity-extraction from text, e.g. using modern Transformer-based Large-Language Models
• Solid understanding of machine learning techniques and their practical applications
• Aptitude for programming in a numerical scripting language (we primarily use Python)
• A meticulous and detail-oriented mind
Nice to have
• Experience using RAGs (Retrieval-Augmentation-Generation)
• Working with financial/trading data
• Experience with C#, C/C++ or Java
• Familiarity with software engineering (version control, unit testing, object oriented-design)
• Degree in Computer Science / Engineering
What we can offer you
• Flat hierarchy and high levels of trust and autonomy
• Exciting problems to solve
• Collaborative team made up of really smart and curious people
• Nice office in Nordhavn with an onsite work model
• Pension, Health Insurance and 30 days of vacation
Practicalities
To apply, please send us your CV and a cover letter telling us why you think this role is a great fit for you. In your cover letter, if applicable, please describe a project where you extracted structured or unstructured information from text - including the techniques, tools, models used and how those extractions informed further decisions/predictions. If you're selected for an interview, we will be very interested in discussing technical details with you about this project!
Should your profile look like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.
If you have questions about the role that you would like clarified before applying, you're welcome to send an email to quant_jobs@alipescapital.com. Please note that applications should not be sent to the email address but rather via the job link.
This job is based in Copenhagen, Denmark and we unfortunately cannot consider remote candidates.