Good knowledge of advanced statistical methods (automotive or manufacturing domain will be an added advantage). Mine and analyze data, applying statistical methods as necessary, pertaining to customers discovery and viewing experiences to identify critical product insights.
Experience in creating statistical models and/or optimization frameworks for improving processes/products/profits
Proactively develop new metrics and studies to quantify the value of different aspects of product.
Translate analytic insights into concrete, actionable recommendations for business or product improvement.
Partner closely with product and engineering leaders throughout the lifecycle of project. Ensure that necessary data is captured; analytic needs are well-defined up front and coordinate the analytic needs.
Drive efforts to enable product and engineering leaders to share your knowledge and insights through clear and concise communication, education, and data visualization.
Should have independently handled a project technically and provided directions to the other Team Members.
Experience in turning ideas into actionable designs.
Able to persuade stakeholders and champion effective techniques through development.
Ongoing technical authority role with our larger customers.
Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company.
Able to lead the project independently.
Technical directions to junior in team, like to sort the respective task for responsible team members.
Expertise with one of the following scripting languages;
o Python, R, Knime, Mat-lab, Java, Mat-lab/Octave
o OpenNLP, WordNet, NLTK
Tech savy and willing to work with open-Source Tools
Applying statistical and machine learning techniques, such as, mean-variance, k-means, nearest-neighbor, support vector, Bayesian time-series and network analysis to identify outliers, classify events or actors, and correlate anomalous sequences of events.
Proven track record and experience with statistical modeling/data mining algorithms such as
o Multivariate Regression, Logistic Regression, clustering algorithms, Support Vector Machines, Decision Trees etc
o Machine learning, or graph mining.
o DOE, Forecasting, Segmentation, Uncertainty Analysis etc.
o Data Mining i.e. Text Mining, Classification Methods SVM, NN, etc
o Vector Space model for Unstructured Text
o Sentiment Analysis, Association Mining, Semantic Analysis