Job Description
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)