Apexon is a digital-first technology services firm backed by Goldman Sachs Asset Management and Everstone Capital. It specializes in accelerating business transformation and delivering human-centric digital experiences. Apexon provides solutions in areas such as digital experience, analytics, AI, and cloud technologies. Additionally, it is recognized as a partner in the Salesforce ecosystem, helping organizations create integrated experiences. Founded in 1996, Apexon is committed to engineering intelligent enterprises

Responsibilities and Duties

• Collaborate with both internal and external stakeholders to identify business needs, prioritize objectives, define key performance indicators, and formulate a data-driven strategy.
• Lead data requirement workstreams with business stakeholders and clients by creating a cohesive process where detailed requirements around data exchange between various systems can be captured at the beginning of a new business initiative.
• Demonstrate leadership and initiative in gathering and analyzing information, structuring findings, and delivering presentations to stakeholders at all levels.
• Utilize machine learning algorithms and statistical techniques to extract insights and patterns from large datasets.
• Explore and experiment with new data sources, technologies, and analytical methodologies to enhance predictive modeling capabilities.
• Develop and deploy data-driven solutions that optimize business processes and improve decision-making processes.
• Collaborate with domain experts to translate business problems into analytical solutions and actionable recommendations.
• Conduct exploratory data analysis to identify trends, anomalies, and opportunities for optimization.
• Evaluate and validate model performance, ensuring accuracy, reliability, and scalability.
• Communicate complex analytical findings and technical concepts to non-technical stakeholders in a clear and concise manner.
• Adhere to project timelines to ensure timely achievement of project goals and objectives.

Technical Skills

• Proficiency in Python for data analysis, manipulation, and modeling.
• Strong understanding of statistical concepts and methodologies for hypothesis testing, regression analysis, and predictive modeling.
• Experience with machine learning techniques, including supervised and unsupervised learning algorithms, neural networks, and ensemble methods, using frameworks such as TensorFlow, PyTorch, or scikit-learn for building and deploying machine learning models
• Familiarity with data visualization libraries such as Matplotlib, Seaborn, or ggplot2 for creating informative and visually appealing visualizations.
• Familiarity with Python data science libraries such as Pandas, NumPy, and Scikit-learn for data manipulation, analysis, and modeling.
• Knowledge of database systems and SQL for data retrieval, manipulation, and storage.
• Understanding of big data technologies such as Hadoop, Spark, or Hive for processing and analyzing large volumes of data.
• Proficiency in data preprocessing techniques such as data cleaning, feature engineering, and dimensionality reduction.
• Experience with version control systems such as Git for managing code repositories and collaboration.
• Ability to work with cloud computing platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and deployment of machine learning models.

Qualifications and Skills

• Bachelor’s degree (Masters preferred) in a discipline such as Computer Science, Applied Math, Applied Sciences, Engineering, etc.
• Experience in Payments Industry would be an asset but not mandatory
• Proven analytical skills in defining business needs into product requirements
• Proven ability to conduct and/or lead multiple projects with minimal oversight
• Excellent communication and interpersonal skills
• Unquestionable personal and business ethics and integrity