Valley Bank
Data Scientist
Skills
20 days ago
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Important information
Contract type:
Permanent
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
1 October 2026
What they need
At Valley Bank, we believe in people's growth potential. We invest in it. We protect it. We focus it. For nearly 100 years, we've been the Bank that clients from every industry turn to for our expertise, strategies, and advice--building the kind of trust that can fuel every goal. We are the leading relationship bank built for growth--with over $60 billion in assets, 3,800 experts, and more than 200 consumer branches and commercial banking offices in communities across the US.
At Valley, we're all driven by an ambition that goes deeper than just having a job. That's why when you work for us, we make it our goal to help you focus on what drives you--working to turn your passions and strengths into assets you can use to propel your ambitions and build the professional legacy you want. Because when we say we're a relationship bank built for growth, that's not just reserved for our clients--that includes all our associates as well.
The Data Scientist will support marketing and digital analytics initiatives. This role is responsible for developing and deploying machine learning and AI models, performing advanced statistical analyses, and transforming large datasets into actionable business insights that drive customer acquisition, engagement, and retention. The position partners closely with marketing, product, and digital teams to deliver data-driven recommendations, build Power BI dashboards, and manage the full analytics lifecycle from data exploration through model deployment and monitoring.
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Responsibilities Include, But Are Not Limited To
- Interpret business needs and requirements and independently perform analysis and/or build reports and dashboards to meet requirements.
- Translate analysis findings and technical topics, visualize data to explain results to a non-technical business audience and senior management.
- Identify new data capabilities to enable strategic objectives, partner with data enablement team to build solutions.
- Interact independently with business partners on data needs and respond to data requests.
- Perform challenging data queries, reconcile data, analyze results, and form conclusions for senior management.
- Drive a strong data-driven culture within the company by mentoring data analysts and increasing data capabilities in other internal functions.
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Required Skills
- Hands-on experience in data modelling, data engineering and data analysis tools such as BI tools, Power BI, SQL, Python (pandas, numpy).
- Working knowledge in developing reports and dashboards in Power BI or Tableau.
- Strong communication, organizational and interpersonal skills, as well as the ability to prioritize and execute multiple objectives.
- Ability to identify key insights and present results to a business audience.
- Preferred experience in mapping techniques, such as calculating distances and routes, as well as ability to build custom market and demographic maps.
- Awareness of latest trends in data analytics.
- Knowledge and experience in the banking industry and banking systems.
- Advanced knowledge of data structures and the ability to visualize data effectively to communicate to a business audience.
- The Data Scientist will have strong collaboration and communication skills to effectively partner with other data teams and business partners.
Required Experience
- Bachelor's degree in a quantitative discipline, such as Business Analytics, Data Science, Mathematics, Econometrics, Engineering, Sciences.
- Miniumum of 3 years working in a data analytics role with hands-on experience in wrangling large data sets, conducting data analysis and developing insights from data.
- Experience working independently with business partners and diverse corporate functions.
Preferred Experience
- Master's degree in a quantitative discipline.
- Financial Services experience and knowledge of Retail/Commercial Banking industry, products, and data highly desired.
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