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Lead Machine Learning

2 months ago

bangalore, India Algonomy Full time
Designation : ML Lead
Experience : 8-10 years
Location : Bangalore
Function: Data Science and Analysis → Data Science / Machine Learning As a team member, you will be offered many opportunities to work on various challenges, such as feature engineering, defining user personas, and ranking the best-suited content for a user's feed based on their interests.
Responsibilities :
• Leading, managing, and developing our team of ambitious decision scientists and facilitating their growth and development.
• Providing day-to-day guidance and feedback to team members to ensure optimal productivity and creativity.
• Planning and executing long-term strategic plans from inception to completion and driving end-to-end processes in collaboration with partners across various teams.
• Ensuring seamless deployment of deep learning and machine learning models.
• Study and transform data science prototypes and design machine learning systems
• Research and implement appropriate ML algorithms and tools
• Run machine learning tests and experiments and perform statistical analysis and finetuning using test results
• Extend existing ML libraries and frameworks, keep abreast of developments in the field
• Collaborate with the engineering team to make pivotal decisions regarding infrastructure, architecture, and scalability
• Work with the product team to incorporate their aims with the machine learning strategy and development
• Communicate deep scientific concepts in understandable language for internal teams and clients • Create systems that benchmark advancement, prevent regressions, and are simple to manage while embracing the challenges of big data, performance, and scalability
• Work with other company leaders to decide on strategies and roadmaps
• Maintain and scale existing technologies
• Stay informed of the latest science, biology, medicine, and machine learning developments
• Serve on the forum / committee to align technology goals to the organizational objectives Requirements:
• A minimum of 8-10 years of experience in modelling and algorithms, with more emphasis on applied ML and research.
• At least three years of experience managing, leading, and developing technical teams, preferably in machine learning.
• Strong proficiency in Python and experience with deep learning frameworks such as Keras, Tensorflow, or PyTorch.
• Proven experience deploying deep learning and machine learning models in a production environment.
• A deep understanding of recommendation systems, ranking, and retrieval algorithms would be advantageous.
• Understanding of data structures, data modelling and software architecture
• Deep knowledge of math, probability, statistics and algorithms
• Ability to write robust code in Python, Java and R
• Excellent communication skills
• Outstanding analytical and problem-solving skills
• BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus ML Skills 1. Classification Models : Logistic regression, Random Forrest, SVM, XG Boost etc 2. Regression Models : Multiple Regression, GLM, Random Forrest Regression 3. Optimization Methods : Heuristic techniques such as genetic optimization, annealing, Knapsack, and other greedy search techniques 4. Clustering Methods, TS forecasting methods : Both parametric and Non Parametric.
About Company:
Algonomy (previously Manthan-RichRelevance) is a global leader in algorithmic customer engagement powering digital first strategies for retailers and brands. With industry-leading retail expertise in connecting demand to supply with a real-time customer data platform as the foundation, Algonomy enables 1:1 omnichannel personalization, customer journey orchestration and customer analytics with Xen AI at its core.
Globally, over 400 retail brands such as HP, L’oreal, Tiffany & Co, Aldi, McDonalds, Zalora and Pizza Hut use Algonomy’s made-for-retail solutions to orchestrate hyper-personalized customer engagement and optimize their merchandising and supplier management. Algonomy, which stands for “systematized knowledge of algorithms”, provides rapid time to value across acquisition, conversion, growth and loyalty with its 300+ pre-built algorithms.
Headquartered in San Francisco and Bangalore, our presence spans over 20 countries. To learn more, please visit