
▷ 3 Days Left Machine Learning Engineer
3 weeks ago
Job Description
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.
- Work across the full analytics lifecycle: from gathering requirements to data preprocessing, modeling, validation, and implementation.
- Break down complex business problems into smaller, manageable components and solve them using ML/AA techniques.
- Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
- Deliver descriptive, predictive, and prescriptive models tailored to business objectives.
- Work on digital transformation initiatives to drive efficiency and innovation through advanced data-driven solutions.
- Prepare and present data insights and analytical outcomes to stakeholders using visualization tools.
Required Skillset:
- Strong proficiency in Python (or R) for data manipulation and model development.
- Hands-on experience with key Python libraries: numpy, pandas, seaborn, matplotlib, sklearn.
- Solid understanding of machine learning models and algorithms, especially in classification and regression.
- In-depth knowledge of algorithms such as Decision Trees, Random Forests, Bagging, Boosting (e.g., XGBoost, LightGBM).
- Understanding of fundamentals of statistics and how they apply to data modeling.
- Experience with Jupiter Notebook and Databricks for model development and experimentation.
- Practical experience in implementing ML models in real business scenarios.
- Ability to align ML/AA solutions with business goals and KPIs.
- Strong problem-solving and critical thinking abilities.
- Experience in stakeholder management.
- Proficiency in presentation and visualization tools: MS Power BI, MS Excel.
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