Epsilon India

Senior Data Scientist

Job description

We are looking for a Sr Data Scientist who is passionate about solving business problems for our clients through the application of data science, with best in class solutions, that also provides us competitive edge. The candidate will have to collaborate/consult with clients and internal teams (Client Support, Product Management) to define, derive, and deploy analytical solutions to solve their business problems. One who is passionate about deriving actionable insight from complex data, can effectively communicate complex problems in simple business terms to stakeholders/clients.

Work location: Bengaluru (Currently, Remote)
Shift timing: 12PM to 9PM

Core Responsibilities

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Develop a use case roadmap for a problem area or capability for the business. Frame the business problem into a Data Science or modelling problem.
  • Extract data from multiple sources. Mine and analyze data from company databases to drive optimization and improvement of product.
  • Work as the data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with Client Support, Product Management and Engineering team to strategize and execute the development of data products.
  • Processing, cleansing, and verifying the integrity of data used for analysis. Undertake preprocessing of structured data.
  • Data mining using state-of-the-art methods. Selecting features, building and optimizing models using ML/AI techniques.
  • Present technical solutions to internal and external stakeholders in a formal setting, effectively communicating key concepts and functionalities
  • Effectively manage stakeholders expectations via direct and frequent communication with high quality results
  • Develop front end deliverable solutions for stakeholders utilizing BI tools such as Tableau, Cognos, Excel, or similar
  • Support internal stakeholders with ad-hoc business problems, charting and reporting
  • Work on multiple assignments concurrently, while handling priorities and challenges and meeting timelines basis project plan and roadmap.
  • Build self-service tools for error detection, diagnosis, and predictive metrics.
  • Build project plans, maintain to-do list, organize work, follow coding ethics, and have an eye for detail

Qualifications

Minimum Qualifications

  • Bachelor’s or Master’s degree in a quantitative discipline (e.g., data science, statistics, economics, mathematics, computer science) or significant relevant coursework/experience
  • 4+ years professional experience in the field of data science or business intelligence
  • Demonstrated proficiency in PYTHON/SCALA/SQL and BIG DATA technologies and the proven ability to program in big data/cloud technologies such as AWS & SPARK; minimum 3 years of experience
  • Experienced with Machine Learning algorithms such as logistic regression, linear regression, lasso regression, k-means, random forest; minimum 2 years of experience
  • Able to produce elaborate documents/narrative suggesting actionable insights and recommendations leveraging BI tools such as Tableau
  • Expertise with Microsoft Office products; including Excel, PowerPoint, Word
  • Great communication skills. Excellent written and verbal communication skills for coordinating across teams.
  • Manage solution development through scrum philosophy, by using JIRA effectively
  • Self-driven and results oriented. Willing to stretch to meet tight timelines.
  • Strong team player with ability to collaborate effectively across geographies/ time zones
  • Good understanding of Digital Marketing in Retail, Finance or Travel Industry

Desirable Qualifications:

  • Professional experience working with R
  • Professional experience working with Power BI, Cognos, Dash, Looker, Domo
  • Professional experience in multi-touch attribution, market mix modelling, fraud analytics, customer journey, churn modeling, customer segmentation, hypothesis testing, a/b testing and recommendation engines.

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