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Data Science Manager

As a Data Science Manager, 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 tools to generate actionable insights from a variety of client data sources. You will focus on solving business problems while working with structured as well as unstructured data. Dealing with ambiguity, yet providing a structured approach to resolve client’s business issues will be a key requirement in this client-facing role.

Responsibilities

Client Interaction and Management

  • Understanding the client objective and managing client expectations on projects along with the Account Manager
  • Independently work with client to scope and deliver on projects as a part of larger team or individually, as required
  • As part of a larger team, align requirements on different work streams and tasks assigned by the client
  • Independently lead client calls

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.
Data Science Manager

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)
  •  5-7 years of relevant experience in Analytics as a Data Scientist. Knowledge of Retail Analytics domain is required. Relevant analytics experience in Operational and Sales Analytics is a plus
  • Certification in Data Science coursework from internationally recognized platforms will be a plus
  • Performance metrics in Kaggle and Analytics Vidhya Data Science competitions will be a plus

Skills Needed:

  • Experience mapping business question and translate the client requirement to data mining and draw insights that answer client question
  • 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 (any one)
  • 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.), building models for data analysis and their real-world advantages/drawbacks.
  • Detailed knowledge of data handling (mining) is required
  • Experience of handling 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). Knowledge of unstructured databases (MongoDB) will be a plus
  • Able to work with Data visualization & communication tools such as TIBCO Spotfire, Tableau, Power BI and Qlikview

Must haves:

  • SQL, R, Python, Tableau/other dashboarding tools, Basic Excel, Basic PowerPoint
  • Ability to build data flows/API integrations with other systems
  • Demonstrated work with business problem solving, automation, and dashboarding within the data science context
  • Written and verbal communication for extensive client handling
  • People management experience
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