Job ID: 303886690
Job date: 2017-05-04
End Date:
Company : dunnhumby Country : Role : Research Scientist
Job date: 2017-05-04
End Date:
Company : dunnhumby Country : Role : Research Scientist
Job Description:
With 100s of millions of weekly data points, collected from our clients, the ways that we can generate value by creatively looking at data are vast. The Data Scientist role is an integral member of this team and you will be involved in hands-on research and development of data-driven solutions to real world problems. The work will encompass both improvements to existing products through innovative use advanced techniques as well as development of completely new offerings using Big Data tools. At dunnhumby you won't be only a data scientist. You'll be part of a culture that welcomes participation and discussion at all levels. You'll be able to see your impact in what we deliver day-to-day to our clients. Key Responsibilities -Research new data modelling, machine learning and data mining techniques for application across functions such as recommender systems, optimisation, pricing , time series forecasting, uplift evaluation, AB testing, Natural Language processing, computer vision, clustering and segmentation. -Research and evaluate new datasets (like clickstream, geo-location and market research) – undertaking data discovery and exploration to improve results. -Leverage state-of-the-art Big Data tools (such as Hadoop, Spark, Python, R) and techniques to build innovative solutions using appropriate modelling techniques and data sets with a focus on implementation. -Develop and embed improvements to data science processes, in particular around building, deploying and monitoring. -Explore different ways for data visualisation with tools like d3.js or tableau. -Look creatively at our data challenges and map out the best approaches to tackle them using the state of art machine learning. Skills, Knowledge & Experience Essential: -Masters or preferably PhD in Computer Science, Artificial Intelligence, Machine Learning, Applied Statistics, BioInformatics, Physics, Engineering or equivalent field -Experience in data analysis or data mining preferably with Python, R or similar Desirable: -Has contributed to large scale programs, undertaking complex analysis, interpreting and presenting back results in a clear and concise manner. -Experience developing/deploying models in to high capacity production environments -Experience with retailers’ data would be useful but is not essential. -Proven track record of applying advanced statistical models and machine learning algorithms to solve a variety of complex problems Skills: Essential: Knowledge of at least 1 programming language suitable for data analysis, ideally python or R (in a data science context, either creating propensity models, segmentations or solving complex problems using optimization techniques). -Other languages such as Matlab, Java, Scala, C are welcome too. Practical experience in relevant machine learning and data modelling techniques used in supervised problems such as decision trees, Random Forests, Gradient boosted machines, linear/logistic regression, deep learning or unsupervised problems such as clustering and dimensionality reduction. -Good ability to interpret business requirements, translate into data science problems and deliver high value outputs. -Ability to work quickly and iterate through trial-and-error, rather than spending an excessive amount of time designing the most robust methodology to deploy at the outset -Ability to make data tell a story through data presentation / visualisation tools and techniques Desirable -Data manipulation using SQL syntax -Familiarity with linux systems -Spark, Hadoop and cluster technologies. -Tensorflow and the theano Personality Essential: -Passionate about tackling difficult questions and building innovative data services using Big datasets. -Creative problem solver with an inquisitive nature. -Drive and discipline to get things done. -Ability to communicate well and discuss complex topics with both technical and business audiences. -Keen attention to detail. -Highly innovative, flexible and self-directed, but also a co-operative team player.
Additional Info:
dunnhumby uses machine learning and data science approaches to improve customer understanding and help drive our clients’ growth. We have a group of advanced data scientists in a Global Data Science division focused on generating innovative products and services to deliver sustained competitive advantage for us and our partners.[Click Here to Access the Original Job Post]
With 100s of millions of weekly data points, collected from our clients, the ways that we can generate value by creatively looking at data are vast. The Data Scientist role is an integral member of this team and you will be involved in hands-on research and development of data-driven solutions to real world problems. The work will encompass both improvements to existing products through innovative use advanced techniques as well as development of completely new offerings using Big Data tools. At dunnhumby you won't be only a data scientist. You'll be part of a culture that welcomes participation and discussion at all levels. You'll be able to see your impact in what we deliver day-to-day to our clients. Key Responsibilities -Research new data modelling, machine learning and data mining techniques for application across functions such as recommender systems, optimisation, pricing , time series forecasting, uplift evaluation, AB testing, Natural Language processing, computer vision, clustering and segmentation. -Research and evaluate new datasets (like clickstream, geo-location and market research) – undertaking data discovery and exploration to improve results. -Leverage state-of-the-art Big Data tools (such as Hadoop, Spark, Python, R) and techniques to build innovative solutions using appropriate modelling techniques and data sets with a focus on implementation. -Develop and embed improvements to data science processes, in particular around building, deploying and monitoring. -Explore different ways for data visualisation with tools like d3.js or tableau. -Look creatively at our data challenges and map out the best approaches to tackle them using the state of art machine learning. Skills, Knowledge & Experience Essential: -Masters or preferably PhD in Computer Science, Artificial Intelligence, Machine Learning, Applied Statistics, BioInformatics, Physics, Engineering or equivalent field -Experience in data analysis or data mining preferably with Python, R or similar Desirable: -Has contributed to large scale programs, undertaking complex analysis, interpreting and presenting back results in a clear and concise manner. -Experience developing/deploying models in to high capacity production environments -Experience with retailers’ data would be useful but is not essential. -Proven track record of applying advanced statistical models and machine learning algorithms to solve a variety of complex problems Skills: Essential: Knowledge of at least 1 programming language suitable for data analysis, ideally python or R (in a data science context, either creating propensity models, segmentations or solving complex problems using optimization techniques). -Other languages such as Matlab, Java, Scala, C are welcome too. Practical experience in relevant machine learning and data modelling techniques used in supervised problems such as decision trees, Random Forests, Gradient boosted machines, linear/logistic regression, deep learning or unsupervised problems such as clustering and dimensionality reduction. -Good ability to interpret business requirements, translate into data science problems and deliver high value outputs. -Ability to work quickly and iterate through trial-and-error, rather than spending an excessive amount of time designing the most robust methodology to deploy at the outset -Ability to make data tell a story through data presentation / visualisation tools and techniques Desirable -Data manipulation using SQL syntax -Familiarity with linux systems -Spark, Hadoop and cluster technologies. -Tensorflow and the theano Personality Essential: -Passionate about tackling difficult questions and building innovative data services using Big datasets. -Creative problem solver with an inquisitive nature. -Drive and discipline to get things done. -Ability to communicate well and discuss complex topics with both technical and business audiences. -Keen attention to detail. -Highly innovative, flexible and self-directed, but also a co-operative team player.
Requeriments :
- M.Sc. or higher Degree in Bioinformatics
- M.Sc. or higher Degree in Computer Science
- Master's Degree in Engineering
Skills :
- Data Mining
- Lunix/Unix
- Machine Learning
- Modeling
- Programing in Python
- Programing Skills
- Programming in Java
- Programming in Matlab
- Programming in R
- SQL
Areas :
Additional Info:
dunnhumby uses machine learning and data science approaches to improve customer understanding and help drive our clients’ growth. We have a group of advanced data scientists in a Global Data Science division focused on generating innovative products and services to deliver sustained competitive advantage for us and our partners.[Click Here to Access the Original Job Post]