Product Sales Specialist - Evidential Data, Parameta Solutions

TP ICAP Group Plc.•New York, NY

47d•Hybrid

About The Position

The Evidential Data Product Sales Specialist will play a pivotal role in shaping Parameta Solutions' data-driven decision-making and commercial strategy. This role is central to the collection, validation, and interpretation of OTC derivatives data, enabling the business to generate compelling insights that underpin our evidential data offering. The Specialist will combine deep knowledge of OTC derivatives markets with advanced technical and analytical skills to ensure our datasets are robust, reliable, and actionable. By delivering high-quality analysis and collaborating with internal stakeholders across sales, product, risk, and strategy, this role will strengthen Parameta Solutions' position as a trusted provider of market intelligence. The successful candidate will be a proactive problem-solver with strong commercial awareness, capable of translating complex datasets into meaningful narratives that resonate with both technical and non-technical audiences. This is an exciting opportunity for someone passionate about data and financial markets to influence strategic outcomes and enhance the value of our global data offering.

Requirements

Bachelor's or Master's degree in a quantitative field (e.g., Data Science, Statistics, Mathematics, Computer Science, Economics, Finance).
Demonstrated understanding of OTC derivatives markets, including how instruments are structured, traded, and priced.
Strong SQL expertise and experience querying/managing large, complex datasets.
Proficiency with business intelligence and visualization tools (e.g., Power BI, Tableau).
Proven ability to analyze complex data, identify meaningful insights, and make data-driven recommendations.
Strong written and verbal communication skills, with the ability to simplify complex findings for diverse stakeholders.
High standards of accuracy and quality control in data handling and reporting.
Experience working in cross-functional teams and building strong stakeholder relationships.
Ability to handle confidential information with discretion and professionalism.

Nice To Haves

Previous experience in a broker, trading, or market infrastructure environment, ideally with exposure to OTC data products.
Familiarity with statistical or data science programming languages (e.g., Python, R).
Cloud & Data Platforms: Working knowledge of cloud-based data storage and warehousing (e.g., AWS, Azure, Snowflake).
Understanding of valuation, risk metrics, and quantitative finance methodologies.
Demonstrated interest in emerging data trends, technologies, and tools relevant to financial markets.
Progress toward or completion of relevant certifications (e.g., CFA, FRM, IMC, or advanced data science/analytics qualifications).

Responsibilities

Maintain a broad and deep understanding of the OTC derivatives markets, including instrument structures, pricing methodologies, and the needs of key client personas for OTC data.
Identify, source, and collect relevant quantitative and qualitative data from internal trading systems, external databases, APIs, surveys, and market records.
Validate, transform, and cleanse data to ensure accuracy, completeness, and consistency.
Conduct detailed analysis to detect trends, patterns, and anomalies. Build reports, dashboards, and visualizations to present insights clearly and persuasively.
Translate analytical findings into actionable business recommendations that support product development, sales strategy, and client engagement.
Partner with cross-functional teams to understand data requirements and deliver tailored analysis, ensuring stakeholders are equipped with relevant and timely insights.
Design and enhance data collection, validation, and reporting processes to drive efficiency, reliability, and scalability.
Ensure all data handling, analysis, and reporting practices comply with legal, regulatory, and internal security standards.
Stay current with emerging technologies, tools, and methodologies in data science and financial analytics, proposing new approaches to strengthen evidential data strategy.

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