Digital-senior Analyst- Data Scientist Sa @ Vijay Deonath Kuwar

Job Description

The ideal candidate must possess strong communication skills, with an ability to listen, comprehend information, and share it with all the key stakeholders, highlighting opportunities for improvement and concerns, if any. He/she must be able to work collaboratively with teams to execute tasks within defined timeframes while maintaining high-quality standards and superior service levels. The ability to take proactive actions and willingness to take up responsibility beyond the assigned work area is a plus. Senior Analyst Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or. with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4+ years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality

Employement Category:

Employement Type: Full time
Industry: IT Services & Consulting
Role Category: Application Programming / MaintenanceClient Server
Functional Area: Not Applicable
Role/Responsibilies: Digital-senior Analyst- Data Scientist Sa

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Keyskills:   communication skills collaboration time management data science problem solving design thinking algorithms prototyping project management storytelling visualization client engagement interpersonal skills R Python SQL SAS clustering classification analytical skills data visualization Tableau QlikView consulting logistic regression speech analytics data cleansing data preparation quality listening comprehension proactive responsibility tech stack decision tree random forest statistical techniques multivariate regression marketmix models survival models churn models image analytics attention to detail