Identify problems, develop ideas and propose solutions within different situations requiring analytical, evaluative or constructive thinking in daily work and for assigned programs and projects
Translate advanced business analytics problems into technical approaches that yield actionable recommendations, in diverse functional domains; communicate results and educate others through insightful visualizations, reports and presentations
Lead teams to analyze and model structured or unstructured data and implement algorithms to support analysis using advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research
Deliver projects/work on time, on budget, in a way that client goal is accomplished
Assist in the planning and delivering of multiple projects.
Strong leadership skills with the ability to adapt to challenges and to mentor team members
Prepare and present ideas and recommendations to colleagues and upper management and aid less experienced employees as an advisor
Apply conceptualized and creative-thinking expertise toward possible reporting solutions or alternatives
Act as the accountable person for the statistical methods used to enquire data sets, design of Machine Learning models & defining the end-to-end data lifecycle of a data science project from ideation to production
Travel to client locations as per the project and/or client needs
Qualifications
Bachelor’s degree in Computer Science, Information Technology, or similar field of study
3-5 years of experience in consulting and technology services designing, deploying, and maintaining high-performance data and analytics solutions using agile methodology
3-5 years of experience in one or more of the following sectors – Restaurants & Food Services, Energy / Oil & Gas, Construction or Manufacturing
3-5 years of full stack data science experience with technologies such as Azure ML, R, Python, Streaming Analytics, Snowflake, Microsoft Azure, Microsoft Synapse, Power BI and Tableau; certifications preferred
Working knowledge for Machine Learning using time series forecasting models, using Deep Learning approaches like RNN, LSTMs
Experienced in building relationships with executives, senior leaders and business decision-makers, existing relationships a plus
Strong traditional mathematics and statistics background and skillset including Bayesian Statistics, multi-variate analysis, hypothesis testing, Maximum Likelihood Estimation (MLE), Markov Chain Monte Carlo Simulation, Gaussian Processes and Genetic Algorithms
Actively participate in conferences / seminars to market and promote services
Outstanding communication (verbal and written) and presentation skills