Analyst in Applied Intelligence
An Analyst in Applied intelligence -understands the importance of sound analytical decision-making, relationship of tasks to the overall project, and executes projects in the context of a business performance improvement initiative.
Duties and Responsibilities:
Ability to work with large data sets and present conclusions to key stakeholders; Data management using R/Python/Spark
Support, monitor and manage all aspects of daily activities with
Working through the phases of project
Define data requirements for creating a model and understand the business problem
Clean, aggregate, analyze, interpret data and carry out quality analysis of it
Set up data for predictive/prescriptive analysis
Development of AI/ML models or statistical/econometric models.
Working along with the team members
Looking for insight and creating a presentation to demonstrate these insights
Supporting development and maintenance of proprietary marketing techniques and other knowledge development projects
Educational Background/qualifications B Tech/M Tech from reputed engineering colleges Masters/M Tech in Computer Science Master degree in Statistics/Econometrics/ Economics from reputed institute M.Phil/Ph.D in Statistics/Econometrics or related field.
Requirements: Responible for taking up day-to-day activities for making deliverables to the ClientDuties and Responsibilities: Act as a Data Scientist for data handling, extraction, manipulation; creating structured form of data and pulling tangible insights from data Take inputs from the Manger/Consultant to develop statistical models (predictive modeling, forecasting etc.) and apply appropriate techniques such as Exploratory Analysis, Regression, Segmentation etc. Prepare summary of results for in-house discussion and take feedback whenever/wherever required Develop executive dashboards to present the analytical insights derived from the data analysis
Proficiency & Experience: 1-3 years of experience Strong ability to extract strategic insights from large data sets Adept with using Statistical (like forecasting/modeling, data analysis, regression/optimization models), Machine Learning (GBM, Decision Trees etc.) & AI techniques (Deep Learning)
Skills: Proficient in data handling suites PYTHON, Spark, R, HIVE, SAS, SQL, or similar packages Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical business people Strong aptitude, ability, motivation and interest in placing quantitative analysis in the context of marketing and business economics. Adept with knowledge & working on Visualization tools like Tableau, POWER BI, etc.Soft Skills Strong problem soling skills Good team player Attention to details Good communication skills