Lead Data Scientist

Job Description

Position: Lead Data Scientist (5 Days WFO)

Experience Level:5 - 8 years

Who we are:

LUMIQ is the leading Data and Analytics company in the Financial Services and Insurance (FSI) industry. We are trusted by the world&aposs largest FSIs, including insurers, banks, AMCs, and NBFCs, to address their data challenges. Our clients include 40+ enterprises with over $10B in deposits/AUM, collectively representing about 1B customers globally.

Our expertise lies in creating next-gen data technology products to help FSI enterprises organize, manage, and effectively use data. We have consistently challenged the status quo, introducing many industry-firsts like the first enterprise data platform in Asia on cloud for a regulated entity.

Founded in 2013, LUMIQ has now completed a decade of innovation, backed by Info Edge Ventures (a JV between Temasek Holdings of Singapore and Naukri) and US-based Season 2 Ventures.

Our Culture:

At LUMIQ, we strive to create a community of passionate data professionals who aim to transcend the usual corporate dynamics. We offer you the freedom to ideate, commit, and navigate your career trajectory at your own pace.

Culture of ownership empowerment to drive outcomes.

Our culture encourages &aposTech Poetry&apos combining creativity and technology to create solutions that revolutionize industry. We trust our people to manage their responsibilities with minimal policy constraints. Our team is composed of the industry&aposs brightest minds, from PhDs and engineers to industry specialists from Banking, Insurance, NBFCs, AMCs, who will challenge and inspire you to reach new heights.

Job Summary:

We are seeking a Sr. Data Scientist to join our team to analyze complex datasets, develop machine learning models, and provide data-driven insights to support business decisions.

Key Responsibilities:

Data Analysis & Exploration

- Perform comprehensive exploratory data analysis (EDA) on large datasets.
- Identify patterns, trends, and anomalies in data.
- Conduct statistical analysis to validate business hypotheses.
- Create data visualizations to communicate findings effectively.
- Assess and ensure data quality and integrity.
- Write complex SQL queries to extract and manipulate data

Machine Learning & Modeling

- Design and develop machine learning models for business problems like (XG Boost, Logistic Regression, DNN, RNN etc)
- Implement supervised and unsupervised learning algorithms
- Perform feature engineering and selection
- Evaluate model performance using appropriate metrics
- Deploy and monitor machine learning models in production

Programming & Development

- Develop data analysis scripts and automation tools using Python
- Build data pipelines and ETL processes
- Create reusable code libraries and functions
- Maintain version control and documentation standards

Required Qualifications

Technical Skills

- SQL: Advanced proficiency in writing complex queries, joins, subqueries, and database optimization
- Python: Strong programming skills in Python for data analysis and machine learning
- Exploratory Data Analysis: Expertise in EDA techniques, statistical analysis, and data visualization
- Machine Learning: Solid understanding of ML algorithms, model evaluation, and validation techniques
- Statistics: Knowledge of statistical methods, hypothesis testing, and experimental design
- Knowledge of any cloud like AWS, GCP or Azure is good to have
- Familiarity with version control systems
- Experience with containerization and deployment tools

Good to Have:-

- Worked on GenAI based Projects
- Using GenAI for driving productivity in your work.
- Knowledge of PySpark is a plus

Must have skills

- Python 2+ years
- Panda - 2+ Years
- Must have led one end to end project
- Must have customer facing experience
- This person will manage a project as a Tech Lead.
- Must have experience working on ML Algorithms including - Random Forest, XGBoost and Neural networks

Must have Frameworks:

- Scikit Learn
- Any 1 of these 3 is a requirement. Pytorch/Keras/ TensorFlow

Candidate must have worked on atleast 1 end to end machine learning project

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