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Data Science Analyst

As a Data Science Analyst, 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 the client’s business issues will be a key requirement in this client-facing role.

Responsibilities

Client Interaction and Management

  • Understand client objective and manage client expectations on projects along with the Account Manager
  • Independently work with the client to scope and deliver on projects as part of a larger team
  • As part of a larger team, align requirements on different work streams and tasks assigned by the client
  • Lead client calls wherever required

Project Management

  • Make significant contributions to the design of the analytical approach and work plan
  • Ensure smooth project operations – overall project quality and productivity of teams

People Management

  • Build team capabilities to expand account
  • 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

  • Participate in organization-improvement initiatives and activities such as knowledge management
  • Conduct skill-based internal training sessions independently
  • Help the organization scale up by actively participating in recruitment drives at the premises or on campus
Data Science Analyst
  • 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 of using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets
  • Experience of handling and creating data architectures
  • Able to work with Data visualization & communication tools such as Oracle BICS, Adobe Analytics, and Tableau/Power BI
  • Data munging: able to work across different data sources (structured or unstructured)
  • Working knowledge of Relational Database Systems and SQL
  • Excellent client presence and communication skills (written and verbal)
  • Proficiency with MS PowerPoint and MS Excel
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.

Must haves:

  • Advanced Excel, SQL, Python, Tableau
  • Ability to work with Salesforce database and build data flows/API integrations with other systems

Good to have:

  • Marketo
  • Outreach
  • Intact
  • Lifeline-Internal custom accounting system
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