Data Science

Requirements:

• Identify business-wide problems, translate into data science solutions and be responsible for guiding the project team

• Liaise with all business stakeholders effectively from brainstorming data science ideas, developing solutions to deploying application

• Exhibit deep knowledge in operational research and advanced analytics, including knowing how to transform complex data in understandable action items within a business context

• Work closely with business stakeholders in automating and building appropriate process visualizations for operational support

• Collect, analyze, screen and manipulate data sets required for modelling and support all decision-making process

• Perform exploratory data analysis and develop proof-of-concept solution using advanced analytics/algorithms, machine learning artificial intelligent models, mathematical optimization etc

• Conduct testing / validation of Machine Learning models, model tuning and parameter optimization

• Work with Cloud based Big Data platforms and tools to design and deploy applications in collaboration with a global IT team

• Integrate data from multiple sources, such as databases, APIs, or streaming platforms, to provide a uni ed view

• Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency

• Identify and resolve data quality issues, monitor data pipelines for errors, and implement data governance and dframeworks

• Enforce data security and compliance with relevant regulations and industry-speci c standards

• Implement data access controls, encryption mechanisms, and monitor data privacy and security risks

• Optimise data processing and query performance by tuning database con gurations, implementing indexing straleveraging distributed computing frameworks

• Optimize data structures for e cient querying and develop data dictionaries and metadata repositories

• Identify and resolve performance bottlenecks in data pipelines and systems

• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders

• Document data pipelines, data schemas, and system con gurations, making it easier for others to understand anthe data infrastructure

• Monitor data pipelines, databases, and data infrastructure for errors, performance issues, and system failures

• Set up monitoring tools, alerts, and logging mechanisms to proactively identify and resolve issues to ensure the and reliability of data.

QUALIFICATIONS & EXPERIENCE :

• At least 3 years of experience working as Data Scientist with proven record of building ML/AI models applied to asset management topics, within the energy/utility or a related industry, and embedding these solutions into business processes

• Experience with formulating and solving problems in an optimization framework, standard types of optimization problem, optimization algorithms development

• Pro cient in advanced statistical methods, Arti cial Intelligence (AI) / Machine Learning (ML)/ Statistical & mathematic , time-series/AI based forecasting, feature engineering, dimensionality reduction, model optimization

• Strong programming skills in Python/R/C or any other related programming languages

• Experience in implementing scalable solutions using R/Python/Scala/Spark/Hadoop on batch & real-time data and development Cloud platforms using different PAAS services

• Experience in identifying, accessing and handling various data sources using a wide variety of tools (API/SQL)

• Working experience with ML,Ops, DevOps, CI/CD frameworks

• Working experience with advanced ML/AI techniques eg. NLP & Deep Learning is a plus

• Experience in implementing scalable software systems and knowledge of the principles of fault-tolerance, reliability an

• Demonstrable experience in delivering end-to-end data science projects, collaborating directly with both technical and business stakeholders

• Experience in formalizing business problems as machine learning solutions and translating into actionable insights and

• Exhibit interpersonal /communication skills to communicate effectively and articulate thought clearly


PREFERRED SKILLS & CHARACTERISTICS

• Team player with good interpersonal, communication, and problem-solving skills

• Able to present complex subjects clearly and coherently to non-domain experts

• Bachelor's or master's degree in computer science, information technology, data engineering, or a related eld

• Strong knowledge of databases, data structures, algorithms

• Proficiency in working with data engineering tools and technologies including knowledge of data integration too. Apache Kafka, Azure IoTHub, Azure EventHub), ETL/ELT frameworks (e.g., Apache Spark, Azure Synapse), big data platform. Apache Hadoop), and cloud platforms (e.g., Amazon Web Services, Google Cloud Platform, Microsoft Azure)

• Expertise in working with relational databases (e.g., MySQL, PostgreSQL, Azure SQL, Azure Data Explorer) and data warehousing concepts.

• Familiarity with data modeling, schema design, indexing, and optimization techniques is valuable for building e scalable data systems

• Proficiency in languages such as Python, SQL, KQL, Java, and Scala

• Experience with scripting languages like Bash or PowerShell for automation and system administration tasks

• Strong knowledge of data processing frameworks like Apache Spark, Apache Flink, or Apache Beam for efficient large-scale data processing and transformation tasks

• Understanding of data serialization formats (e.g., JSON, Avro, Parquet) and data serialization libraries is valuable

• Having experience in CI/CD and GitHub that demonstrates ability to work in a collaborative and iterative develop environment

• Having experience in visualization tools (e.g. Power BI, Plotly, Grafana, Redash)

---