Job TitleClient Job Description: Solid knowledge of various Image Filtering, Binary Morphology, Perspective / Affine transformation, Edge Detection, and Tracking. Machine Learning: Regression, Unsupervised Learning, PCA. Nice but not necessary to have HDR, Panorama, and deep Learning object detection. Apply statistical techniques like regression properties of distributions statistical tests etc. to analyse data. Machine Learning Techniques: Apply machine learning techniques like clustering decision tree learning artificial neural networks etc to streamline data analysis. Creating advanced algorithms: Create advanced algorithms and statistics using regression simulation scenario analysis modelling etc.Expectations from this role: Work with stakeholders creating quick prototypes of the solution to define analytics roadmap. Work with business to understand business domain and convert business problems into analytics problems.
Create or use existing frameworks to test and validate new models. Explain models and put results in easy to interpret manner such that non-analytic person can understand. Turn data into information that can improve current workflow or processes that will help make better business decisions. Generate business insights to help clients with decision making. Adhere to best practices of coding.Typical performance measures: Schedule Adherence Quality of code and other deliverables Number of reusable components developed New analytics solutions that got approved for further development.Performance Areas: Statistical Techniques: Apply statistical techniques like regression, properties of distributions, statistical tests, etc. to analyse data. Machine Learning Techniques: Apply machine learning techniques like clustering, decision tree learning, artificial neural networks, etc. to streamline data analysis.
Creating advanced algorithms: Create advanced algorithms and statistics using regression, simulation, scenario analysis, modelling, etc. Data Visualization: Visualize and present data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc. Management and Strategy: Oversees the activities of analyst personnel and ensures the efficient execution of their duties. Critical business insights: Mines the business's database in search of critical business insights and communicates findings to the relevant departments. Code: Creates efficient and reusable code meant for the improvement, manipulation, and analysis of data. Version Control: Manages project codebase through a version control tool e. g. git, bitbucket, etc.
Predictive analytics: Seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis Prescriptive analytics: Attempts to identify what business action to take Create Reports: Create reports depicting the trends and behaviours from the analysed data Training end users on new reports and dashboards. Set FAST goals and provide feedback to FAST goals of mentees Document: Create documentation for own work as well as perform peer review of documentation of others' work Manage knowledge: Consume and contribute to project related documents, share point, libraries and client universities Status Reporting: Report status of tasks assigned Comply with project related reporting standards and process Solution architecture: Create modular architecture such that it can be reused easily across projects. Analysis: Report trends for anomalies, outliers, trend changes, and opportunities from a given data set Data Gathering: Partner with business and gather relevant data Modelling: Data models and experiments for solving business problems Stakeholder management: Explain findings to both technical and nontechnical stakeholders. New business development: Create solution architecture and quick prototypes to explain analytics roadmap to a business team. Team Management: Increase team productivity by upskilling them technically.