Apptad - ML Data Scientist

Role Overview

In this role you will help drive personalized experiences for customers as a ML Engineer monitoring pipelines batch and ondemand job types to improve Pricing Recommendations

Are you passionate about harnessing the power of data to drive impactful business decisions We are seeking an ML Engineer to play a pivotal role in shaping the future of our consumer journey through cuttingedge Machine Learning ML solutions for pricing and recommendations Join us and make a tangible difference in the lives of our customers by developing innovative solutions that deliver personalized experiences and optimize value

This is a remote and contract only position

About The Role

Ability to attend meetings and discussions during overlapping XXXX Standard Time XST hours musthave

ML acumen to conceptualize design and implement stateoftheart ML models for dynamic pricing strategies and personalized product recommendations

Strong grasp of understanding difference between data pipelines and ML pipelines

Develop implement and deploy machine learning models that leverage our unique combination of user behavior and subscription data to improve consumer value from our products

Engineer and maintain largescale consumer behavioral feature stores while ensuring scalability and performance

Develop and maintain data pipelines and infrastructure to support efficient and scalable ML model development and deployment

Collaborate with crossfunctional teams Marketing Product Sales to ensure your solutions align with strategic objectives and deliver realworld impact

Create algorithms for optimizing consumer journeys and increasing conversion and monetization

Design analyze and troubleshoot controlled experiments Causal AB tests Multivariate tests to validate your solutions and measure their effectiveness

Agile development mindset appreciating the benefit of constant iteration and improvement

Focus on business practicality and the 8020 rule very high bar for output quality but recognize the business benefit of having something now vs perfection sometime in the future

About You

Bachelors degree in Computer Science or related fields Master or PhD in Machine Learning Statistics Data Science or related quantitative fields preferred

5 years of experience in one or more of the following areas machine learning engineering including deep learning recommendation systems pattern recognition data mining or artificial intelligence

Proficient in Python SQL intermediate data engineering skill set with tools libraries or frameworks such as MapReduce Hadoop Spark Hive and Big Data technologies scikitlearn Keras TensorFlow PyTorch PySpark etc

Experience in Databricks is preferred

Experience with various ML techniques and frameworks eg data discretization normalization sampling linear regression decision trees deep neural networks etc

Experience in building industrystandard recommender systems and pricing models

Experience in MLOps ML Engineering and Solution Design

Its Great But Not Required If You Also Have

Experience working in a consumer or B2C space for a SaaS productsoftware provider

Experience in developing recommendation systems and deep learningbased models

Excel in solving ambiguous and complex problems being able to navigate through uncertain situations breaking down complex challenges into manageable components and developing innovative solutions

Machine Learning-Python