▷ Apply in 3 Minutes: Data Scientist

Job description

About Business Unit:

Powerful predictors of the future - our Analytics team seamlessly blends data science and business intelligence to provide unparalleled foresight for our platform offerings.

They turn insights into actionable results for our clients by collaborating with senior team members and staying ahead of market trends, powered by our data assets.

By using new-age analytic tools and emerging technologies, the team cultivates a dynamic learning environment for curious minds to thrive.

Who we are looking for?

At Epsilon, our people use real human insights to find solutions that empower some of the biggest brands in the world.

Our team is now growing, and we are on the lookout for dedicated individuals who use descriptive, predictive and prescriptive analytics to impact consumer behaviour every day.

So, are you someone who enjoys leading conversations with influential stakeholders to help clients understand the value of their investments?

Then you could be exactly who we are looking for.

Apply today and be part of a creative, innovative and versatile team who constantly share insights, solve problems and create the remarkable.

What you’ll do?

The Digital Analytics team in the Client Analytics Group works on client engagements and related delivery for People Cloud Prospect & Discovery environments.

The team also partners with client consulting team and platform team and data providers, using analytics and data science to drive strategic thought and effective decision making.

The Data Scientist is responsible for conducting data analyses using Python/SQL/PySpark and other tools in support of a variety of analytic solutions.

Click here to view how Epsilon transforms marketing with 1 View, 1 Vision and 1 Voice.

Responsibilities

Operational

- Perform hands-on analysis on large volumes of customer’s first-party data and third-party data to provide statistically valid analysis and related Master and perform all steps required to create analysis-ready datasets, including data integration/merging, variable preparation, and quality control (QA/QC)
- Provide proficient problem solving and data analysis, derived from modelling and statistical experience
- Design and Implement Machine learning models using Spark ML and Python/Pyspark
- Create engaging and meaningful data visualizations / power point presentations of findings linked to clear client business impact.
- Present statistical results to both technical and non-technical audience in a clear manner
- Participate in the design, planning & execution of projects
- Own end to end implementations of Marketing machine learning models such as Customer Segmentation, Propensity models, CLTV etc.

Functional

- Become proficient with Epsilon data assets
- Document and articulate steps taken in an analysis to project managers.

Follow all policies and procedures for programming, project documentation, and system management
- Be an active learner - learn new and powerful tools, technologies, algorithms and methodologies to be at the edge of data science learnings
- Collaborate well with cross-functional internal teams as needed to drive results
- Effectively manage time and resources in order to deliver on time / correctly on a limited number (1-4) of concurrent projects.
- Proactively communicate with supervisor regarding workload and the status of assignments and manage partners effectively.

Qualifications

- Bachelor’s degree, or higher, in a quantitative discipline (e.g., Engineering, Statistics, Economics, Mathematics, Marketing Analytics) or significant relevant coursework
- 4-9 years of experience in the analytics and data science; marketing analytics experience preferred
- Strong experience with Python, SQL and Microsoft office packages
- Must have hands-on experience with machine learning and statistical techniques like Logistic regression, Decision trees, Random Forest, K-means clustering etc.
- Experience in distributed computing using PySpark, comfort with DataBricks and experience in machine learning with Spark / MLlib
- Strong analytic thought process and ability to interpret findings
- Acute attention to detail (QA/QC)
- Excellent verbal and written communication skills
- Highly motivated and collaborative team player with strong interpersonal skills
- Effective organization and time management skills
- Passion for understanding key business problems, bringing together a team to understand data/ instrumentation needs and/or mine through data to unearth deep insights into customer experiences
- Proven capability to deliver end-to-end analyses by asking the right questions, extracting data, and building predictive models to ensure actionable results

Required Skill Profession

Mathematical Science Occupations