Manager Data Scientist Client Analytics

Epsilon; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Epsilon in Bengaluru, India, is seeking a skilled Manager, Data Scientist to lead and mentor a team in leveraging machine learning and deep learning techniques. This role involves guiding the development of predictive models and data science solutions for our platform offerings.

Ideal candidates will possess a strong background in data science and at least 5 years of experience in managing teams. Epsilon promotes diversity and is an Equal Opportunity Employer committed to inclusion.

Qualifications

• 10-12 years of total experience with 5+ years of managing and leading data science teams.
• Strong experience in at least one programming language (Python, R, C, C++).
• Expertise in predictive analytics and machine learning algorithms and techniques.

Responsibilities

• Provide guidance to Data Scientists and manage machine learning and deep learning projects.
• Work with the team to analyze complex data structures and perform statistical analysis.
• Own end-to-end implementations of multiple marketing machine learning models.

Job description

About the Role

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

PeopleCloud Customer is a world‑class cloud‑based Customer Data Platform (CDP) fully enabled with a complete Marketing Automated Operating System (MAOS). The team is looking for a skilled Manager, Data Scientist who is an expert, mentor and advocate. This role requires strong machine learning and deep learning background, proficiency in Python, Spark MLLib, Tensorflow, Keras, ML algorithms and Deep Neural Networks, Big Data, and a passion for transforming data into ML models. You will work with a distributed team and directly with clients to own data science solutions as part of the COSMOS Cognitive Marketing Intelligence Cloud Platform team.

Responsibilities

• Provide guidance to Data Scientists and manage machine learning and deep learning projects.
• Work with the team to analyze complex data structures, manipulate, cleanse data, and perform statistical analysis.
• Design and guide machine learning models using Spark ML, Python, HDFS, and DataBricks.
• Design and implement deep neural network models using Tensorflow, PyTorch, Keras, and Python.
• Develop machine learning pipelines with big data design principles in MS Azure cloud using Azure Data Factory.
• Own end‑to‑end implementations of multiple marketing machine learning models such as churn, CLV, propensity, and affinity models.

Qualifications

• Strong passion for understanding key business problems and bringing together a team to unearth deep customer insights.
• Proven capability to deliver end‑to‑end analyses by asking the right questions, extracting data, and building predictive models.
• Expertise in predictive analytics, statistical modeling, data mining, machine learning algorithms and techniques (classification, clustering, regression, multivariate testing).
• Excellent communication and interpersonal skills.
• MS in Computer Science, Math, Physics, or equivalent education or professional experience.
• 10‑12 years of total experience with 5+ years of managing and leading data science teams.
• Strong experience in at least one programming language (Python, R, C, C++).
• Experience working with code repositories and continuous integration tools (Git, Jenkins).

Equal Opportunity Statement

Epsilon is an Equal Opportunity Employer. Epsilon is committed to promoting diversity, inclusion, and equal employment opportunities by using reasonable efforts to attract, recruit, engage and retain qualified individuals of all ethnicities and backgrounds, including, but not limited to, women, people of color, LGBTQ individuals, people with disabilities and any other underrepresented groups, traits or characteristics.