**Company: Adriane Maps GmbH Job Description Summary: Ariadne is looking for a Senior Data Scientist to join their team, working with cutting-edge technology to develop ML solutions for brick-and-mortar businesses. The role involves problem framing, data collection and cleaning, exploratory data analysis, and model development. Requirements include a PhD/MSc in a quantitative discipline, hands-on experience in data-driven solutions, and proficiency in Python, Git and SQL. Additional skills in data engineering and Apache Hadoop are appreciated. The benefits include flexible working hours, permanent employment in a fast-growing company, and a great company culture with team events and creative freedom. Job Description: Ariadne is seeking a highly skilled Senior Data Scientist to join our growing team. You will have the opportunity to work with cutting-edge technology, collaborate with a team of talented analysts and developers to build innovative ML solutions, and help shape the future of brick-and-mortar businesses to meet our client’s needs. As a member of the Data Science team, you will take on some of our biggest challenges and your work will impact the entire Ariadne ecosystem. Our team moves very fast, so you’ll have the opportunity to make an immediate difference in device fingerprint, localization, and speed clustering spaces. Tasks Problem Framing: Define and scope complex business problems into specific data science questions or projects. Data Collection & Cleaning: Gather, preprocess, and clean large volumes of data from various sources to make it suitable for analysis. Exploratory Data Analysis (EDA): Analyze and visualize data to discover patterns, trends, correlations, and outliers. Model Development: Build and deploy machine learning models using various algorithms and techniques. Requirements PhD/MSc in Physics, Maths, Statistics, Data Science, Computer Science, Engineering, or other quantitative discipline At least 3-5 years of hands-on experience developing and applying data-driven solutions in a corporate or consulting setting would be greatly appreciated. Strong experience with exploratory data analysis & data modelling to derive valuable insights and develop hypotheses, PoC which should lead to production models. Experience with Supervised & Unsupervised modelling, Mathematical Optimization techniques (LP/MIP/NLS/Stochastic), localization & sessionization, and/or Networks modelling Proficiency in Python, Git & SQL Additional competence in data engineering, noSQL, Apache Hadoop, Spark or Tensorflow, is appreciated but not required. Self-initiative - be able to independently take initiatives without much direction. Deep belief in data and ability to rally people behind your findings/recommendations. Benefits Flexible working hours – we’re focused on getting the job done. Permanent employment in a fast-growing SaaS company step-changing the location intelligence industry. Awesome team and company events – because the fun part should not be neglected. Great company spirit: flat hierarchies, a lot of creative freedom, working independently, and, of course, a cool team.
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
