The Data Systems department are looking to place a dynamic and creative individual who can make a strong contribution to our team and systems. Research and develop detailed analysis techniques to utilise the data sources and combine the data to find relationships using state of the art methods and lead deployment of future analytic methods. Enthusiastic, confident, willing to learn, collaborative & energetic.
Our placement students will also have the opportunity to familiarize themselves with developing tools to improve the live operational activities and the post-event analysis & checks; design and develop GUI supporting live & replay operational tasks. Engage in the continual assessment and review of systems and operations, making proposals for improvement. Ability to demonstrate practical applications and utilization of data analytic work / mathematical and/or statistical reduction on datasets Development of bespoke data analytical and visualization tools Excellent knowledge and skills in machine learning and computer vision Good working knowledge of IT, Networking, communications, software systems etc.
Join us and work alongside data scientists, geospatial experts and other data specialists in developing, deploying and running data products that deliver tangible insight to the business to help understand, quantify and manage geographic risk. We will also consider equivalent experience; Programming experience, ideally in Python; Familiarity working with spatial data and databases; Familiarity working with containers and in cloud environments; Understanding of statistical concepts and data science methodologies; Knowledge of insurance useful but not essential. We don't expect you to be familiar with them all, and will provide opportunity and support to learn those that become most relevant to your role. Python libraries for spatial analysis and mapping (e. We also offer flexible working options, global career opportunities across the wider Allianz Group, and fantastic career development and training. We have a range of employee networks focusing on gender inclusion, cultural diversity, LGBTQIA+, disability and long term health conditions (including neurodiversity), intergenerational and life stages, parents and carers, mental wellbeing, menopause support and armed forces and veterans, all supporting you to bring your best and authentic self to work.
Reporting to the Lead Data Scientist, you will be part of the Commercial Analytics team operating both as an individual contributor as well as a part of a larger delivery team, with a need to task manage more junior DS as needed. Join us, and a competitive salary is just the beginning. It's one of our core values and that's why we're taking the lead when it comes to creating a diverse, equitable and inclusive future - for our people, and the wider global sports betting and gaming sector.
As a GROW graduate you will be empowered to drive your career and will be exposed to a variety of experiences to assist you in gaining the skills you require to succeed. Our Commitment to Equality, Diversity, Inclusion & Belonging We want you to be able to bring your best self to work every day which is why we take equality and inclusion seriously and hold ourselves to account for our actions.
We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team. Promote and share the team's work, methods, and skills in data science, causal inference, and machine learning with team members and the broader SIE community Stay up to date on the latest advancements in the field of data science (including causal inference and machine learning) and share knowledge and new ideas with team. BA/BS Degree in Mathematics, Applied Math, Statistics, Computer Science is a minimum requirement In-depth understanding and experience using supervised and non-supervised machine learning techniques Understanding of causal inference methods (such as propensity score matching, synthetic control methods, and difference-in-differences) for accurately estimating causal relationships Proficiency in designing and performing hypothesis tests to validate or reject research hypotheses Experience with standard BI Tools (Tableau, MicroStrategy, etc. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
Harmonic Security, a cutting-edge startup with joint headquarters in the UK and US, is leading the charge in data protection for the future. Your keen eye and meticulous approach will ensure data accuracy and completeness, a vital foundation for robust and reliable models. A desire to work in a fast-paced, innovative environment. Been in front of customers and/or end-users to build a complete understanding of the problem domain. Shared Success: Everyone holds stock options, where we all share in the success of the company.
Bottomline is a global leader in business payments and cash management, with over 30 years of experience and moving more than $10 trillion in payments annually. We're proud to be an equal opportunity employer, committed to creating an inclusive and open environment for everyone.
You will work closely with the Data Engineering team to ensure the deployment, integration, and scaling of these models within our data infrastructure. Experiment with a variety of algorithms and techniques to enhance model accuracy and performance. Collaborate with the data engineering team to guarantee that clean, well-structured data is available for model training and evaluation. Engage in rigorous testing and validation processes to ensure models are ready for scaling and integration across various business applications. Collaborate with the data engineering team to ensure that the necessary infrastructure and pipelines are in place to support machine learning initiatives. Make data-driven recommendations for model improvements and adapt to changes in data or business needs. Familiarity with AWS cloud services, particularly those relevant to data science and machine learning. Proficiency in data wrangling, feature engineering, and developing scalable machine learning solutions. Knowledge of deep learning techniques and their application to real-world problems.
Our Compliance Data Strategy aims to encourage data-led decisions to mitigate regulatory risk, improve regulatory and customer outcomes, and present these insights effectively to stakeholders Our goal is to bring more value from a business perspective through data insights, as well as a significant uplift in data analytics in our assurance and control testing, which now needs a dedicated individual to drive this work. Use AI/ML and data science techniques to reduce the need for manual work in the compliance space, including analysis of structured numerical data and application of LLMs and similar tools to unstructured data. An understanding of the importance of team culture, and a demonstrable ability to act as a role model to maintain a culture of curiosity, support and honesty. We've made a promise to each other and every employee; to focus on sustainable impact, to care about each other's wellbeing, to use our diverse expertise to be curious and optimistic and to develop the skills needed for our future.