Job Deatils

• Number of Vacancies : 1

• Total Experience : 3

• Skills : Project Management , SQL Server, NoSQL, Excel, Retail Analytics, Data Mining, Data Visualization, Machine Learning , Data Science , Sales Analytics

• Industry : Mining

• Functional Area : Others

• Qualification : Others

• Specialization : Others

Job Description

As a Data Scientist, you will be working on client specific projects and will be expected to understand the client data architecture. You will be required to use different technical skills and variety of tools to generate actionable insights from a variety of client data sources. Your focus shall remain on solving business problems while working with structured as well as unstructured data. Dealing with ambiguity, yet providing a structured approach to resolve clients business issues will be a key requirement in this client facing role. Background: Graduate with an engineering degree (preferably Computer Science) or a degree in statistics/math with experience in coding or equivalent Post Graduate with analytical pedigree (preferably Operations Research, Econometrics or MBA equivalent with analytical electives) 1-2 years of relevant experience in Analytics as a Data Scientist (Anlayst) . Knowledge of Retail Analytics domain is required. Relevant analytics experience in Operational and Sales Analytics is a plus. Key Skills: Written and verbal communication for extensive client handling Proficiency with MS PowerPoint and MS Excel Ability to build domain expertise across industries and implement Data Science use cases, accordingly Should definitely be comfortable with SQL, R, Python, Tableau/PowerBI/others Detailed knowledge of data handling (mining) is required Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Experience mapping business question and translate the client requirement to data mining and draw insights that answer client question. Experience working with and creating data architectures / data farms (from different data formats into a consolidated data base) Data munging: able to work across different data sources (structured or unstructured) Able to work with Data visualization & communication tools such as TIBCO Spotfire, Tableau, Power BI and Qlikview Detailed knowledge of Relational Database Systems and SQL and working knowledge of noSQL databases (MongoDB) Must haves: SQL, R, Python, Tableau/other dashboarding tools, Basic Excel, Basic Powerpoint Ability to work with Salesforce database and build data flows/API integrations with other systems Demonstrated work with business problem solving, automation, and dashboarding within the data science context People management experience is surely a plus Role and Responsibilities: Project Management Making significant contributions to the design of the analytical approach and work plan Being responsible for smooth project operations overall project quality and productivity of teams People Management Build team capabilities through training and knowledge sharing to expand account and data science group Manage team as the account expands/new accounts are acquired Mentor individuals and impart skills by way of trainings and on-the-job coaching Other Initiatives Assist other Data Science teams with client work if you have a skill or insight that may be wanting in the other team Participating in organization-improvement initiatives and activities such as knowledge management Conducting skill-based internal training sessions independently Helping the organization in scaling up by actively participating in recruitment drives at the premises or on campus.