Lead Analyst

We are seeking a highly qualified data science professional with extensive experience in building both supervised and unsupervised Machine Learning models, including Regression, Classification, Segmentation, and Time Series Forecasting. The ideal candidate will excel in conducting detailed Exploratory Data Analysis (EDA) and subsequently developing various models for prospect identification.

Job Description:

Key responsibilities include:

• Performing comprehensive EDA to uncover insights and inform model development.
• Develop and maintain statistical models leveraging Machine Learning algorithm using Python/ Spark /R etc. This involves designing, implementing, and optimizing statistical models to ensure efficient model performance, writing and maintaining complex SQL queries to extract, transform, and load (ETL) data from various sources, and ensuring data integrity and accuracy throughout the model building process.
• Generate insights and reports from the existing models to support business decision-making. This includes analyzing data trends and patterns to provide actionable insights, preparing comprehensive reports that summarize key findings and recommendations, and presenting data-driven insights to stakeholders to inform strategic decisions.
• Experiment with the iterative model development cycle (CRISP-DM Methodology). This involves developing new features based on business needs and requirements, exploring multiple alternative approaches using ML algorithms, and writing efficient, scalable code following best practices.
• Applying basic machine learning models to enhance data analysis, using libraries such as scikit-learn and TensorFlow for model development and evaluation, and interpreting and communicating the results of machine learning models to stakeholders.
• Conducting ad-hoc analyses to support business needs.
• Delivering end-to-end modelling solutions to clients, from requirement gathering to final implementation.
• Engage directly with the client to understand business/marketing objectives.
• Ensure adherence to data governance policies and compliance with relevant regulations.
• Work with various internal and external stakeholders to develop project plans, manage day-to-day tasks, and meet project deadlines.
• Perform a cyclic recalibration of the existing models in production to achieve better performance in terms of higher accuracy, efficiency and scalability.
• Provide guidance and training to junior analysts and team members.

The successful candidate will join a dynamic and growing audience analytics team dedicated to developing advanced analytic solutions for leading companies across various industries.

Qualifications:

• 3 to 5 years of experience in statistical modeling and machine learning algorithms, with a proven track record of delivering impactful data science projects in a fast-paced environment.
• Bachelor's or Master's degree is required in any of the below streams:
  • Mathematics
  • Statistics
  • Economics
  • Finance
  • Business Management
  • Engineering

Must Have:

• Proficient in Python, PySpark and SQL.
• Expertise in Machine Learning algorithms such as XGB, LightGBM, GBM, RF, K-Means etc.
• Knowledge of advanced statistical methods and their applications.
• Familiarity with MLOps practices for continuous integration and deployment of ML models.
• Ability to work with APIs for data extraction and integration.
• Experience with visualization tools such as Tableau or Power BI.
• Proficiency in Excel Reporting.
• Strong communication skills, capable of articulating complex data insights clearly to both technical and non-technical stakeholders.
• Demonstrated ability to solve open-ended questions and handle ad-hoc data requests with creative problem-solving and a proactive approach.
• Ability to work independently and collaboratively within a team, managing multiple tasks simultaneously.
• Solid understanding of fundamental machine learning concepts and techniques, with hands-on experience using libraries such as numpy, pandas, scikit-learn, matplolib, seaborn and TensorFlow.
• Domain-specific knowledge in Retail or CPG or Digital Media, or Pharma, with the ability to apply industry insights to generate relevant data solutions and recommendations.

Good to Have:

• Experience with Databricks and Snowflake.
• Knowledge of Natural Language Processing (NLP) and LLMs.
• Designing and analysing A/B tests to inform business decisions.
• Knowledge of R.
• Basic ETL knowledge.
• Experience with cloud-based databases such as GCP/Big Query.
• Expertise in creating business presentation using PowerPoint.
• Experience with project & team management.

Location:

DGS India - Bengaluru - Manyata N1 Block

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent