Job Responsibilities

● Work on end-to-end data science lifecycle: from building proof-of concept models to production-ready models & work with engineers to deploy them to production

● Execute and take ownership of deep learning projects end-to-end. Good exposure to various deep learning algorithms and frameworks

● Should be able to effortlessly switch between roles of an Individual Contributor, team member, and data science manager as demanded by each project.

● Managing analysts on the project- work distribution and timeline planning for the projects, training and guiding the analysts

● Be able to manage business people and excellent in pitching your work

● Figure out gaps in existing products and adding intelligence to improve it

● Designing the frameworks in data sciences (R, Python, Azure ML, Amazon ML, Google

ML, Spark etc) to be used for relevant projects

● Timely interfacing with the vendors in resolving their asks and queries along with testing and verifying their deliverables and refining them.

● Keep updated on latest research in AI and deep learning and find ways in which it can be used to solve business problems

● Must be able to read research papers (eg: some novel architectures, training techniques,

etc.) and be able to implement it fully to solve our specific problems

Technical Skill Set

● Expert user of Python, R and SQL

● Hands-on experience in handling unstructured (image, video, audio) and build solutions using Deep Learning / Machine Learning

● Experience in implementing object detection, GAN’s. Knowledge of reinforcement learning is a plus.

● Good grasp and detailed knowledge of any one deep learning library (PyTorch,

Tensorflow, Caffe etc.) is a must





● Experience with Data Visualization tools like Tableau, Microsoft Power BI and

SiSense

● Exposure to working on AI/Data Science/Analytics platforms likeMicrosoft AI,

Amazon AI, IBM WATSON, H20, Knime

● Strong business acumen to understand business objectives & dynamics and possess excellent written and verbal communication skills for coordinating across teams

● Experience in analysing complex problems and translating them to data science algorithms with due attention to computational efficiency and testing at scale.

● Experience in machine learning, supervised and unsupervised:Forecasting,

Classification, Data/Text Mining, NLP, Decision Trees,

● Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural

Networks, Deep Learning Algorithms.

● Experience in statistical learning: Predictive & Prescriptive Analytics, Parametric and Non-parametric models, Regression,

● Time Series, Dynamic / Causal Model, Statistical Learning, Guided Decisions,

Topic Modeling

● Strong hold of concepts in Statistics and expertise in Machine Logs Processing,

text mining and text analytics

● Self-motivated, ability to handle ambiguity

● Strong problem solving skills

Essential Qualification

Masters/PhD in a Quantitative & Engineering disciplines - Mathematics,

Statistics, Physics, Computer Science, Electronics, and Data Mining etc.

BE/BTech

Requirements

Essential Qualification

Masters/PhD in a Quantitative & Engineering disciplines - Mathematics,

Statistics, Physics, Computer Science, Electronics, and Data Mining etc.

BE/BTech

Experience

​

● 7-9 years of robust experience in data mining, machine learning and statistical analysis

● Prior experience in implementing production-level deep learning projects is a must

📌 Senior Lead Data Scientist (Mumbai)
🏢 GreenThumbs
📍 Mumbai