DTICI_Senior Data Science engineer_T8 II 950

# Senior Data Science Engineer ## Company Overview \[Company overview was not provided in the original description.\] ## Job Summary We are looking for a **Senior Data Science Engineer** to join our Advanced Analytics and Big Data Team. The main purpose of this role is to generate insights that enable data-driven decision making within the finance and financial services domain. ## Responsibilities - **Problem Definition**: Collaborate with stakeholders to translate business goals into clear, data-focused questions and define project scope and success metrics. - **Data Collection and Preparation**: Gather, clean, and preprocess data from diverse sources, ensuring data quality and consistency, while engineering features to enhance model performance. - **Exploratory Data Analysis (EDA)**: Utilize statistical methods and visualization techniques to uncover trends and validate assumptions, summarizing key insights for business alignment. - **Model Building and Evaluation**: Select, train, and refine models suited to the business problem, evaluating performance with relevant metrics and documenting model assumptions. - **Deployment and Monitoring**: Work alongside engineering teams to deploy models, establish performance monitoring, retrain models as necessary, and incorporate feedback to improve accuracy. ## Qualifications - **Educational Background**: Graduated with a B.Tech/M.Tech in a quantitative Statistics from a top-rated university. - **Technical Skills**:\ Strong experience in Statistics\ ML/DL/Optimization+Gen AI(U can look for profiles into Statististics as a part of curriculum Eg.BSc/MSc statistics or Econometrics - **Experience**: Minimum of 4-7 years of relevant experience focusing on advanced analytics and big data. - **Model Development**: Proven experience in end-to-end model development to deployment and performance monitoring. - **Technical Skills**: - Strong knowledge of Applied AI, Machine Learning (ML), and Deep Learning techniques. - Proficient in at least one programming language, preferably Python or PySpark. - Deep knowledge of machine learning algorithms including tree-based methods, clustering, regression, and classification techniques. - In-depth understanding of statistical concepts such as probability distributions, statistical tests, correlation analysis, and descriptive statistics. - **Communication Skills**: Excellent communication skills to convey insights clearly to both technical and non-technical audiences. - **Stakeholder Management**: Ability to manage different stakeholders and handle multiple projects simultaneously. - **Problem Solving**: Strong analytical skills to transform business problems into data science problems. ## Preferred Skills - Advanced experience with Spark, Databricks, or the Azure technical stack. - Experience with model deployment to cloud or on-premises environments. - Good communication and presentation skills. ## Experience - Minimum of 4-7 years of relevant experience in data science, focusing on end-to-end data analysis and model building. ## Environment \[Typical work setting or location details were not provided in the original description.\] ## Salary \[Salary information was not provided in the original description.\] ## Growth Opportunities \[Information regarding growth opportunities was not provided in the original description.\] ## Benefits \[Information regarding benefits offered was not provided in the original description.\]