Location
Chennai | India
Job description
Lead Data Scientist
Job location: Chennai (Work from Office) Job Type: Fulltime
Experience: 8 Years Job Summary:
We are looking for Data Scientists to lead a data science team and help us gain useful insight out
of raw data.
Lead Data Scientist responsibilities include managing the client data science team planning projects and building analytics models. You should have a strong problemsolving ability and a knack for statistical analysis. If you re also able to align our data products with our business goals we d like to talk to you.
Your ultimate goal will be to help improve our AI services by making the most out of our client s data.
Responsibilities
- You would be required to Identify develop and implement the appropriate statistical techniques algorithms and Deep learning / ML Models to create new scalable solutions that address business challenges across industry domains.
- Define develop maintain and evolve data models tools and capabilities.
- Communicate your findings to the appropriate teams through visualizations
- Collaborate and communicate findings to diverse stakeholders
- Provide solutions for but not limited to: Object detection/Image recognition natural language processing Sentiment Analysis Topic Modeling Concept Extraction Recommender Systems Text Classification Clustering Customer Segmentation & Targeting Propensity Modeling Churn Modeling Lifetime Value Estimation Forecasting Modeling Response to Incentives Marketing Mix Optimization Price Optimization.
- Ability to build train and lead a team of data scientists.
- Follow/maintain an agile methodology for delivering on project milestones.
- Excellent oral presentation and written communication skills.
- Experience applying statistical ideas and methods to data sets to answer business problems.
- Mine and analyze data to drive optimization and improvement of product development marketing techniques and business strategies.
- Working on ML Model Containerisation.
- Creating ML Model Inference Pipelines.
- Testing and Monitoring ML Models.
Tech Stack:
- Strong Python programming Knowledge Data Science and Advanced Concepts like Abstract Class Function Overloading Overriding Inheritance Modular Programming and Reusability
- Cloud Experience in using Azure services
- REST API using Flask or fastapi frameworks
- Good to have Pyspark: Spark Dataframe Operations SQL functions API Parallel Execution
- Good to have Unit testing using Python pytest or Unittest
Preferred Qualifications:
- Bachelors/ Masters/ PhD degree in Math Computer Science Information Systems Machine Learning Statistics Applied Mathematics or related technical degree.
- 6 plus years total experience with minimum of 3 years of experience in a related position as a senior data scientist building Predictive analytics Computer Vision and NLP solutions for various types of business problems.
- Advanced knowledge of statistical techniques machine learning algorithms and deep learning frameworks like Tensorflow Keras Pytorch
- Programming background and expertise in building models using at least one of the following languages: Python R
- Strong individual planning and project management skills able to juggle multiple tasks and priorities.
- Selfmotivated and driven to deliver agreed results ontime
- Ability to convert analytical output into clear concise and persuasive insights & recommendations for technical & nontechnical audience
- Strong influence and relationship management skills.
Key traits:
- Should have excellent communication skills.
- Should be self motivated and willing to work as part of a team.
- Should be able to collaborate and coordinate with onshore and offshore teams.
- Be a problem solver and be proactive to solve the challenges that come his way.
r,fastapi,flask,rest,clustering,pytorch,statistics,nlp,fine-tuning,tensorflow,visualizations,inheritance,keras,forecasting,python,overriding,ml models,raw data,data science,abstract class,parallel execution,artificial intelligence,python pytest,concept extraction,propensity modeling,function overloading,machine learning,predictive analytics,topic modeling,statistical analysis,computer vision,recommender systems,sentiment analysis,deep learning,churn modeling,azure services,object detection,text classification,price optimization,marketing mix optimization,machine learning algorithms,sql functions api,data annotation tools,building analytics models,ml model containerisation,spark dataframe operations,natural language processing,lifetime value estimation,mine and analyze data,modeling response to incentives,ml model inference pipelines,define, develop, maintain and evolve data models
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