COGENT Infotech
Overview
The team has been managing the Data Platform and Engineering Analytics for the past 3 years. They are now looking to backfill a position to support advanced use cases involving prediction, NLP, and AI/ML, particularly around: Customer retention/Revenue generation/Subscription analytics/Churn analysis/Feature impact analysis. The role is focused on Telematics use cases for Toyota and Lexus, especially on the subscription side—understanding customer behavior during trial periods and optimizing user experience. Responsibilities / What you’ll be doing
Expertise in Machine learning and Data Science. Experience working with large datasets, finding insights, and telling stories using data. Understanding of advanced ML topics (Deep learning including CNNs, RNNs, NLP, Transformers, GANs, LLMs is a plus). Experience with ELT/ETL processes using tools such as AWS Glue and related transformations. Experience working with automotive data sets is preferred. Deep expertise in data science tasks such as data segmentation, churn analysis, repeat purchase, market basket analysis, A/B testing, etc. Skills
5 years in Data Science 2–3 years in AI/ML Hands-on coding (Python, SQL) Strong AWS experience (Azure/GCP not acceptable) Familiarity with Cloud Llama Nice to have: TensorFlow, PyTorch, Jupyter Notebooks, SageMaker Git, CI/CD pipeline Soft Skills
Ability to analyze customer behavior and feature releases Strategic thinking for customer acquisition and retention Capable of walking through relevant use cases Other Preferences
Prior Toyota experience is a plus Onsite preferred (100%), hybrid (3–4 days) acceptable Two rounds of interviews planned Requirements
What we’re looking for: Skilled in forecasting and leading data science projects to leverage data to make better business decisions by delivering customer-centric insights. You will lead AI/ML efforts using an analytical mindset with critical thinking data skills. What you’ll be doing
Work on ad-hoc data science projects Experience with large datasets, finding insights, and telling stories using data Experience working with advanced ML topics (Deep learning, NLP, Transformers, LLMs) is a plus Experience with ELT/ETL processes using Glue, Glue transforms Experience working with automotive data sets is preferred Deep expertise in data science viz. data segmentation, churn analysis, repeat purchase, market basket, A/B testing, etc. Qualifications / Must Haves
Strong technical skills in SQL, Python, R, or other programming languages used in data analysis Working knowledge of CI/CD and MLOps (Git, Docker) Good knowledge of distributed datastores (SQL, NoSQL) and Big Data and Cloud technologies (GCP, BigQuery, Firebase, Snowflake, Redshift) Successful completion of one or more assessments in Python, Spark, Scala, or R; using open source frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Preferred / Added bonus
Understanding of model management frameworks and familiarity with at least 3 models (e.g., Claude, LLAMA, Haiku, Gemma)
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The team has been managing the Data Platform and Engineering Analytics for the past 3 years. They are now looking to backfill a position to support advanced use cases involving prediction, NLP, and AI/ML, particularly around: Customer retention/Revenue generation/Subscription analytics/Churn analysis/Feature impact analysis. The role is focused on Telematics use cases for Toyota and Lexus, especially on the subscription side—understanding customer behavior during trial periods and optimizing user experience. Responsibilities / What you’ll be doing
Expertise in Machine learning and Data Science. Experience working with large datasets, finding insights, and telling stories using data. Understanding of advanced ML topics (Deep learning including CNNs, RNNs, NLP, Transformers, GANs, LLMs is a plus). Experience with ELT/ETL processes using tools such as AWS Glue and related transformations. Experience working with automotive data sets is preferred. Deep expertise in data science tasks such as data segmentation, churn analysis, repeat purchase, market basket analysis, A/B testing, etc. Skills
5 years in Data Science 2–3 years in AI/ML Hands-on coding (Python, SQL) Strong AWS experience (Azure/GCP not acceptable) Familiarity with Cloud Llama Nice to have: TensorFlow, PyTorch, Jupyter Notebooks, SageMaker Git, CI/CD pipeline Soft Skills
Ability to analyze customer behavior and feature releases Strategic thinking for customer acquisition and retention Capable of walking through relevant use cases Other Preferences
Prior Toyota experience is a plus Onsite preferred (100%), hybrid (3–4 days) acceptable Two rounds of interviews planned Requirements
What we’re looking for: Skilled in forecasting and leading data science projects to leverage data to make better business decisions by delivering customer-centric insights. You will lead AI/ML efforts using an analytical mindset with critical thinking data skills. What you’ll be doing
Work on ad-hoc data science projects Experience with large datasets, finding insights, and telling stories using data Experience working with advanced ML topics (Deep learning, NLP, Transformers, LLMs) is a plus Experience with ELT/ETL processes using Glue, Glue transforms Experience working with automotive data sets is preferred Deep expertise in data science viz. data segmentation, churn analysis, repeat purchase, market basket, A/B testing, etc. Qualifications / Must Haves
Strong technical skills in SQL, Python, R, or other programming languages used in data analysis Working knowledge of CI/CD and MLOps (Git, Docker) Good knowledge of distributed datastores (SQL, NoSQL) and Big Data and Cloud technologies (GCP, BigQuery, Firebase, Snowflake, Redshift) Successful completion of one or more assessments in Python, Spark, Scala, or R; using open source frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Preferred / Added bonus
Understanding of model management frameworks and familiarity with at least 3 models (e.g., Claude, LLAMA, Haiku, Gemma)
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