Job Description

Job Purpose

As a key member of our Data Science team, you will be responsible for developing innovative AI & ML solutions
across diverse business domains. This includes designing, implementing, and optimizing advanced analytics models
to address complex business challenges and drive data-driven decision making. Your core responsibility will be to
extract actionable insights from large datasets, develop predictive algorithms, and create robust machine learning
pipelines. You will collaborate closely with cross-functional teams including business analysts, software engineers,
and product managers to understand business requirements, define problem statements, and deliver scalable
solutions. Additionally, you'll be expected to stay current with emerging technologies and methodologies in the AI/ML
landscape to ensure our technical approaches remain cutting-edge and effective.

Desired Skills and experience

Demonstrated expertise in applying advanced statistical modeling, machine learning algorithms, and deep

learning techniques.Proficiency in programming languages such as Python data analysis and model development. Proficiency in cloud platforms, such as Azure, Azure Data Factory, Snowflake, Databricks. Experience with data manipulation, cleaning, and preprocessing using pandas, NumPy, or equivalent libraries. Strong knowledge of SQL and experience working with various database systems and big data technologies. Proven track record of developing and deploying machine learning models in production environments. Experience with version control systems (e.g., Git) and collaborative development practices. Proficiency with visualization tools and libraries such as Matplotlib, Seaborn, Tableau, or PowerBI. Strong mathematics background including statistics, probability, linear algebra, and calculus. Excellent communication skills with ability to translate technical concepts to non-technical stakeholders. Experience working in cross-functional teams and managing projects through the full data science lifecycle. Knowledge of ethical considerations in AI development including bias detection and mitigation techniques.

Key Responsibilities

Analyze complex datasets to extract meaningful insights and patterns using statistical methods and machine

learning techniques.Design, develop and implement advanced machine learning models and algorithms to solve business problems

and drive data-driven decision making.Perform feature engineering, model selection, and hyperparameter tuning to optimize model performance and

accuracy.Create and maintain data processing pipelines for efficient data collection, cleaning, transformation, and integration. Collaborate with cross-functional teams to understand business requirements and translate them into analytical

solutions.Evaluate model performance using appropriate metrics and validation techniques to ensure reliability and

robustness.Present findings, visualizations, and recommendations to stakeholders in clear, accessible formats tailored to

technical and non-technical audiences.Stay current with the latest advancements in machine learning, deep learning, and statistical methods through

continuous learning and research.Develop proof-of-concept applications to demonstrate the value and feasibility of data science solutions. Implement A/B testing and experimental design methodologies to validate hypotheses and measure the impact of

implemented solutions.Document methodologies, procedures, and results thoroughly to ensure reproducibility and knowledge transfer

within the organization