Analytics & Insights Consultant

MassMutual•Springfield, MA

17h

About The Position

As an Analytics & Insights Consultant (Advanced), you serve as a trusted analytical partner to Operations leaders, helping translate operational performance into clear insights that inform tactical and strategic decisions. You will work across areas such as New Business, Policyholder Services, and Claims to answer complex business questions, surface risks and opportunities, and ensure leaders understand not just what is happening, but why it matters. This role balances hands-on analytical execution with business partnership. You will respond to high-priority analytical requests, proactively identify areas where deeper insight is needed, and shape analyses that connect operational metrics to service, cost, growth, and experience outcomes. This role requires strong influence, credibility, and accountability for insight quality and clarity. The Analytics & Insights team sits within Business Intelligence and partners closely with Insurance Operations and enterprise stakeholders who rely on operational data. As an advanced-level consultant, you are expected to model strong analytical thinking, business acumen, and effective communication—contributing to a culture where analytics is used to guide decisions, not just report results. You will collaborate closely with peer consultants, data analysts, visualization partners, and business SMEs, and you will provide informal guidance and knowledge-sharing to help elevate overall team capability.

Requirements

5+ years of professional experience in business analytics or consulting roles, evidenced by delivering analysis that supported operational or strategic business decisions.
3+ years of experience supporting Insurance Operations or financial services environments.
3+ years advanced SQL proficiency, demonstrated by the ability to independently write complex queries involving multiple joins, subqueries, aggregations, and transformations across multiple data sources.
3+ years hands-on experience with at least one analytics or BI tool (e.g., Tableau, Power BI, Python, R, Alteryx) used to build repeatable analytical outputs consumed by business stakeholders.

Nice To Haves

Documented experience translating analysis into insights, demonstrated through written summaries, presentations, or executive readouts tailored to non-technical audiences.
Proven ability to independently manage concurrent analytical deliverables, balancing multiple requests while meeting agreed-upon deadlines and quality standards.
Experience operating in ambiguous problem spaces, demonstrated by framing analytical approaches, defining assumptions, and validating results with stakeholders.
Demonstrated ability to connect operational performance to broader business outcomes.
Experience contributing to forecasting, staffing, or scenario-based analyses.
Strong communication skills, including comfort engaging with senior leaders.
A collaborative, solutions-oriented mindset with an interest in mentoring peers and promoting data literacy

Responsibilities

Deliver advanced analytical insights by mining, integrating, and analyzing internal and external data (KPIs, operational results, industry benchmarks, and customer information) to support decision-making.
Translate analysis into business implications, clearly articulating what the results mean for operational performance, trade-offs, risks, and opportunities.
Support and contribute to complex analytics initiatives such as performance diagnostics, capacity or volume analysis, forecasting, and operational efficiency studies.
Apply systems thinking to explain how changes in volume, mix, policy, or process impact service levels, cost structures, and downstream outcomes.
Influence leaders through clear storytelling, participating in—and at times leading—executive readouts and discussions with concise, decision-oriented messaging.
Operate with limited guidance, independently framing analytical approaches while collaborating closely with partners and adjusting based on feedback.
Promote strong analytics practices, including data literacy, KPI clarity, assumptions documentation, and consistent analytical standards.
Mentor and support peers by sharing expertise, reviewing work where appropriate, and contributing to the team’s collective growth.