Data Science Practicioner
Cognizant Analytics Practice
AI & Analytics (AIA) is part of Cognizant Digital Business. Our three key offerings are Data Modernisation, Customer Intelligence, and Operational Intelligence. AIA is responsible for selling (Business Development) and implementing these offerings (Delivery). Out selling point is the way we organize and train our people. The Cognizant skill-pool is extensive and is experienced in coming together to deliver a multidisciplinary solution. It is key we have people with the right skills that are trained on the relevant technologies & methodologies. That is the role of the AIA Guilds and Communities: AIA Architecture, Data Engineering, Data Governance, Data Visualisation, and Data Science.
The Data Science Community is organized by geographies to keep the leaders close to the people they are mentoring and support the local business development effort: UK & Ireland, Germany & Switzerland (DACH), Benelux, Spain & Nordics.
We are looking for a Data Science Practitioner in Madrid. You will be working in a variety of data science settings, using a diverse set of tools to automat computational statistics. Usually the analytics automation is a component of an end-to-end solution and you will collaborate within a multi-disciplinary team. The work the Guild is involved in Europe covers many industries such as Pharmaceutical, Banking, Finance, Insurance, Manufacturing, Retail, Telecommunications, Utilities & Government.
Lately a significant of work we do is in the Cloud using Python. We are in leveraging Cognizant's Evolutionary AI solution (https://www.cognizant.com/ai/evolutionary-ai). We constantly adapt to the market needs and are flexible on the choice of technology. Your Role
This role combines aspects of delivering analytical solutions on customer site or in one of the Cognizant offices, alone or as part of a team. The role will also have a component of 'Go to Market' and pre-sales support relying on your knowledge and encouraging you to learn.
When your career progresses, you will get opportunities to design of analytical solutions, lead delivery of analytical solutions, and people management and mentoring. Key responsibilities:
• Work on delivery project as a member of an experienced consulting team developing and applying advanced analytics & Machine Learning methodologies.
• Prepare presentations and reports on findings as well as recommend next steps to ensure successful project completion
• Seek and develop innovative methods and processes and keep up to date on latest trends, tools and advancements in the area of analytics and data
• Take active part in sales support activities such as responding to RFIs and RFPs - support the proactive and reactive sales process by providing the advanced analytics aspect of presentations and responses to clients.
• Interacting with the wider European Data Science Guild, the rest of the European Guilds and other Cognizant Business Units globally.
• Contribution to & participation in the shaping of the Data Science Guild and its activities
As you develop, you career you will get opportunities to lead and manage teams and become a subject matter expert for an industry or methodology.
• A university degree in Machine Learning, AI, Statistics, or Operations Research area - or the acquisition of such skills through professional experience
• Have at least 3+ years of experience in Data Science field
• Proven, knowledge and deep experience in quantitative methods (machine learning, natural language processing, image detection, predictive analytics, statistical modelling and forecasting) with strong statistical and mathematical background.
• Data exploration and preparation
• Hypothesis Formulation, model building, validation and recalibration
• Consultative approach regarding identifying client issues and commitment to delivering high quality solutions
• Collaborative team player
• Know-how in different statistical programming languages such as Python, R, SAS
• Ability to work autonomously
• Strong written and verbal communication skills in English
• Flexibility to travel
• Optional skills that are nice to have but not mandatory include:
- Knowledge of KNIME, RapidMiner, SPSS Modeler, SAS
- High/Intermediate SQL knowledge.
- Knowledge of Bayesian (Belief) Networks (probabilistic graphical models), Neural Networks, Deep Learning, and Cognitive computing.
- Knowledge of Technologies like ML Azure / Watson/ AWS / SQL / Teradata / Tableau /other visualization platforms
- Knowledge of Agile methodologies
Interested? Please submit an updated version of your resume to email@example.com #Assoc