Data Scientist 1066 views

At DataSparQ they combine data science, design and technology with their clients’ priorities to create intelligent products that make an impact. They want organisations of all sizes to be able to capture value from their data.

Their approach is simple and effective: In their Prime phase, they work with their clients to identify what high-value opportunities can be unlocked with intelligent products – and how viable these are. Priority products are taken into their Prove phase where they quantify the opportunity by demonstrating the data is sufficient, the analysis yields performance, and this can be wrapped in a product the business can use to deliver value. Once the value is proven, they harden the product in their Productionise phase which ensures the product can be scaled and sustained.

Their resulting intelligent products are valuable, usable and sustainable. They are tools and services that integrate into their clients’ workflows: Abstract Programming Interfaces (APIs); interactive applications, bespoke data visualisations or even a simple Excel file – whatever it takes to automate, accelerate or augment their decisions.

Their team is mix of talented, and highly accomplished big data engineers, data scientists, product designers and software engineers. Their products are deployed across the cloud ecosystem and their client base spans multiple industries including retail, finance and gaming.

Job Description

They are looking for talented Data Scientists who have a passion for solving complex business problems with machine learning and advanced statistical methods. As a Data Scientist, you will be involved into development of real-life predictive solutions as well as working with clients to resolve their advanced analytics requirements.

You will work on analytics solutions based on machine learning & statistical predictive algorithms for clients of DataSparQ. You will have hand-on experience in machine and deep learning, statistical modelling and software development, proven scientific research skills and technical leadership.

Responsibilities include:

• Develop machine learning, artificial intelligence, and statistical algorithms and solutions using R and Python.
• Prepare advanced data analyses and present results of these analyses to stakeholders.
• Data transformation activities to perform feature engineering exercises.
• Engage with clients throughout the lifecycle of projects on both advisory and delivery assignments.
• Participate in pre-sales activities to demonstrate how data science and statistics may be applied for commercial advantage of potential clients.
• Develop solution prototypes and deliver CRP (Conference Room Pilot) sessions.
• Help to define the analytics solution architecture from a pragmatic standpoint.
• Support blended teams of colleagues, client and partner resources to help share knowledge and develop an integrated delivery ethic.

Experience Profile

The Ideal candidate will have:

• Commercial and academic experience in developing ML & AI solutions using R and Python;
• In depth knowledge of machine learning algorithms.
• Developed capabilities with data modelling and complex big data analyses.
• Hands-on experience in developing complex query structures with SQL and/or NoSQL systems.
• Strong business analysis skills and deep understanding of analytics.
• Business facing with the skills and a proven consultative approach.
• Has working experience with Cloud AI offerings like Google’s ML engine/AWS SageMaker.

Additional Information

Applications are only invited from candidates with the right to reside and work within the UK. Candidates should be willing to travel for the purposes of client delivery and collaborating with colleagues.

Closing Date for applications: 15th September 2019