Machine Learning Engineer
7 days ago
Machine Learning Engineer
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi
Role: Machine Learning Engineer
Experience Level: 1 to 4 Years
Work location: Mumbai
Role Overview:
We are looking for a Machine Learning Engineer to join our growing Data & Digital team. The role involves contributing to Advanced Analytics (AA), Machine Learning (ML), and data-driven projects aimed at improving business processes across various verticals. The ideal candidate should possess strong technical skills in Python, ML model development, and problem-solving, along with the ability to interact with business stakeholders.
Key Responsibilities:-
Develop and deploy machine learning models (classification & regression) to solve real-world business problems.
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Work across the full analytics lifecycle: from gathering requirements to data preprocessing, modeling, validation, and implementation.
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Break down complex business problems into smaller, manageable components and solve them using ML/AA techniques.
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Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
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Deliver descriptive, predictive, and prescriptive models tailored to business objectives.
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Work on digital transformation initiatives to drive efficiency and innovation through advanced data-driven solutions.
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Prepare and present data insights and analytical outcomes to stakeholders using visualization tools.
Required Skillset:
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Strong proficiency in Python (or R) for data manipulation and model development.
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Hands-on experience with key Python libraries: numpy, pandas, seaborn, matplotlib, sklearn.
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Solid understanding of machine learning models and algorithms, especially in classification and regression.
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In-depth knowledge of algorithms such as Decision Trees, Random Forests, Bagging, Boosting (e.g., XGBoost, LightGBM).
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Understanding of fundamentals of statistics and how they apply to data modeling.
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Experience with Jupiter Notebook and Databricks for model development and experimentation.
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Practical experience in implementing ML models in real business scenarios.
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Ability to align ML/AA solutions with business goals and KPIs.
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Strong problem-solving and critical thinking abilities.
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Experience in stakeholder management.
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Proficiency in presentation and visualization tools: MS Power BI, MS Excel.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us
Experience LevelMid Level-
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