Epsilon India
Bangalore
Epsilon India is looking for a talented team player for the role of Data Scientist for its Marketing Machine learning (MML) Team. We work on state-of-the-art machine learning and data science algorithms and platforms to provide strategic insights to our clients. Some of the technologies we work include Python, PySpark, Horovod, Tensorflow/Keras, databricks, flask, Snowflake and are present on all three clouds – Azure, AWS and GCP. We develop state of the art models like recommender system, marketing models (churn, cltv, segmentation), NLP, image processing, speech detection, and many more. All this is done in a scalable manner and deployed at scale with frameworks like Apache Airflow and Spark.
You will work with a distributed team (onshore and offshore) and work closely with a broadly talented team of data analysts, data scientists, data engineers, cloud experts, data visualizers, full stack developers, etc. You will work directly with clients to own data science solutions as a member of the Data Sciences MML Cloud Services team and will operate as part of the product team to extend the Platform functionality when not supporting client projects.
Roles & Responsibilities
- End to end Machine learning model development – from data collection, to preprocessing, cleaning, modeling, hyperparameter tuning, evaluation, interpretation, and deployment
- Develop and demonstrate proficiency with multiple languages, platforms, algorithm, and verticals. Ability to learn new algorithms and technologies.
- Collaborate with internal/external stakeholders to manage data logistics – including data specifications, transfers, structures, and rules
- Access and extract data from a variety of sources of all sizes (including client marketing databases)
- Provide problem solving and data analysis, derived from programming experience
- Perform as an Individual Contributor as well as mentor and train resources when given a team
- Work on 1 or 2 new projects/methodologies/algorithms in a year as a part of R&D effort
Qualifications
- Bachelor’s or Master’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Economics, Mathematics, Marketing Analytics) or significant relevant coursework. For the right candidate, degree is not a deciding point.
Mandatory Expertise in the following fields:
- Programming language: Python & SQL (Expert Level)
- Machine Learning Algorithms: Linear/Logistic, k-means clustering, decision trees and random forest, KNN algorithm, Boosting (XGBoost) (Expert Level)
- Machine Learning Evaluation : Evaluation parameters (R2, precision , recall, confusion matrix), regularization, hyperparameter tuning(Expert Level)
- Exposure to atleast one cloud environment – AWS/GCP/Azure
Good to have Expertise in the following fields:
- Programming languages: PySpark
- Deep Learning Algorithms: CNN, RNN/LSTM, GRU
- Natural Language Processing
- Exposure to multi Cloud Environment: GCP, Azure, AWS
- Experience with Databricks and Spark, Big Data Technologies (Hadoop/Hive/Scala)
Years of Experience:
- 3-7 years in core data science role
- Only relevant experience in data science role will be considered
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