[OK] Establishing handshake with mehta.intel...
[OK] Loading dataset "AAKASH_J_MEHTA_v2026"...
[OK] Reindexing 6 case files, 24 capabilities...
[OK] Verifying credentials checksum 0x4F2A... OK
> SYSTEM_READY ▮
DECODER_
OPERATIVE: AAKASH_J_MEHTA ROLE: BUSINESS_INTELLIGENCE BASE: BOSTON_MA
00:00:00 EST AVAILABLE
// CODENAME: DECODER BUSINESS INTELLIGENCE OPERATIVE

Aakash
Mehta

"In a world overflowing with information, the real value lies not in collecting data, but in decoding its language — to illuminate patterns, drive intelligent decisions, and solve real-world problems."
SPECIALTY:DASHBOARDS · KPI · FORECASTING · GENAI
RUNTIME:— calculating —
CLEARANCE:OPT / STEM-OPT VERIFIED
DEPLOY ME → VIEW CASE FILES ↓ 2026 FIELD INTEL ↓
IDENTITY_MATRIX ONLINE
DESIGNATIONaakash_j_mehta
PROGRAMM.S. DATA ANALYTICS ENG.
INSTITUTIONNORTHEASTERN UNIV.
GPA / GRAD3.63 / MAY 2025
EX-DEPLOYMENTASTRAZENECA · ALEXION
TARGETINGBUSINESS / DATA / BI ANALYST
RANGEBOS · NYC · CHI · DAL · LA · MIA · TPA · PHX
DECODE
SIGNAL
0X.01 // IMPACT_AGGREGATE SIGNAL/NOISE: 98.4%
S001OK
0%
Snowflake cloud cost reduction
Power BI usage dashboard · Alexion
S002OK
0%
Validation effort eliminated
Enterprise-wide BI replaced manual reporting
S003OK
0%
Forecast accuracy lift
Travel demand · Power BI · Holiday Horizons
S004OK
0%
PM2.5 anomaly detected
Reshaped team analysis · U.S. holidays
S005OK
0%
Diabetes readmission accuracy
Logistic regression · 130 US hospitals
S006OK
0+
GenAI event reach
Co-contributed · Alexion · cross-team
QUANTIFIED OUTCOMES SHIPPED 9
DATA POINTS ENGINEERED 550,000+
0X.02 // IDENTITY_MATRIX DECODE PROFILE
// PROFILE.READOUT  ·  CONFIDENCE: HIGH

I translate ambiguous business questions into quantified outcomes.

M.S. Data Analytics Engineering at Northeastern, with a Computer Science backbone from Mumbai. My work sits at the intersection where stakeholder questions become SQL queries, where dashboards become operating decisions, and where models become cost reductions on a P&L.

Last summer at AstraZeneca’s Alexion, I built a Snowflake usage dashboard that drove a 15% cloud cost reduction and replaced manual reporting across two teams — cutting validation effort by 80%. I co-led a GenAI rollout that reached ~200 employees.

I work fluently across Power BI, SQL, Python, DAX, and modern GenAI tooling. I write code, but my real product is decisions: faster, sharper, and grounded in evidence.

SKILLS_RADAR // 6_AXES ● LIVE
BI / DASHBOARDS SQL / QUERY PYTHON / ML STORYTELLING GENAI / COPILOT FORECASTING
0X.03 // CASE_FILES N=06 · DECLASSIFIED
CASE_FILE / 001 ● SHIPPED

Alexion · AstraZeneca Rare Disease

Business Intelligence Analyst  ·  New Haven, CT  ·  Jun 2024 — Aug 2024
Built a Power BI dashboard monitoring Snowflake usage across the enterprise, surfacing high-cost queries through DAX-driven KPI logic. Partnered with two cross-functional teams to replace a brittle manual reporting flow with self-service BI, freeing leadership cycles. Co-contributed to a GenAI showcase event that reached ~200 employees.
−15%
Cloud Cost
−80%
Validation Effort
~200
GenAI Reach
POWER_BISNOWFLAKEDAXKPI_DESIGNSTAKEHOLDER_OPSGENAI_ROLLOUT
OPEN CLASSIFIED FILE→
CASE_FILE / 002 ● SHIPPED

Holiday Horizons

Travel · Mobility · Air Quality  ·  Mar 2025 — Apr 2025
Fused travel and environmental datasets to investigate U.S. holiday travel pressure on air quality and pricing. Surfaced a 370% PM2.5 spike that reframed the team’s analytical lens. Delivered Power BI dashboards driving a 40% lift in forecast accuracy for sustainability-aware demand planning.
+370%
PM2.5 Spike
+40%
Forecast Acc.
+45%
Decision Speed
POWER_BIFORECASTINGEDASUSTAINABILITYDEMAND_PLANNING
OPEN CLASSIFIED FILE→
CASE_FILE / 003 ● ARCHIVE

Lyric → Genre Classifier

NLP · Multi-class Classification  ·  Mar 2024 — Apr 2024
Trained Random Forest, Logistic Regression, and XGBoost on 500,000 English song lyrics across 5 genres. Engineered TF-IDF features after lower-casing & tokenization. XGBoost shipped at 75.4% accuracy — a clean baseline for downstream lyric-driven recommender systems.
75.4%
XGBoost Acc.
500K
Lyrics
5
Genres
PYTHONXGBOOSTTF-IDFNLPSCIKIT-LEARN
OPEN CLASSIFIED FILE→
CASE_FILE / 004 ● ARCHIVE

Diabetes Readmission Predictor

Healthcare · Predictive Modeling  ·  Feb 2024 — Mar 2024
Modeled a decade-long dataset spanning 130 U.S. hospitals using Random Forest, Gradient Boosting, and Logistic Regression. The logistic model shipped at 88% accuracy and simulated significant readmission reductions through early risk flagging — the kind of model that translates to ICU bed-days saved.
88%
Logistic Acc.
130
Hospitals
−40%
Readmissions*
PYTHONPANDASSEABORNLOGISTIC_REGHEALTHCARE
OPEN CLASSIFIED FILE→
CASE_FILE / 005 ● ARCHIVE

Job Market Intelligence

SQL × NoSQL Analytics Pipeline  ·  Sep 2023 — Dec 2023
Built a hybrid SQL + NoSQL workflow to interrogate underemployment and wage gaps across regional datasets. Pipelines shaved analysis-to-insight time by 40% and improved job-skill matching accuracy — the kind of upstream work that makes downstream dashboards trustworthy.
+60%
Eff. Gain
−40%
Time-to-Insight
2
DB Engines
SQLNOSQLETLDATA_MODELINGLABOR_ECON
OPEN CLASSIFIED FILE→
CASE_FILE / 006 ● ARCHIVE

Course Recommender System

Analyst Intern · SAKEC, Mumbai  ·  Jun 2021 — Oct 2021
Engineered a hybrid collaborative + content-based recommender on 50,000+ data points. Tuned the model and deployment pipeline against real engagement metrics — shipping into a production-ready web application with measurable lift in CTR and a meaningful drop in bounce rate.
+50%
Acc. Lift
+40%
CTR
−20%
Bounce
PYTHONCOLLAB_FILTERINGCONTENT_BASEDWEB_DEPLOYA/B
OPEN CLASSIFIED FILE→
0X.04 // CAPABILITY_MATRIX SYSTEM_INVENTORY
LANGUAGES5
  • Python
  • SQL
  • R
  • DAX
  • MATLAB
BI_PLATFORMS4
  • Power BI
  • Tableau
  • Excel · Pivot · VLOOKUP
  • Dashboard Architecture
DATA_INFRA5
  • Snowflake
  • MySQL
  • NoSQL
  • ETL Pipelines
  • Data Modeling
METHODS7
  • EDA
  • A/B + Hypothesis Testing
  • Forecasting
  • KPI Development
  • SWOT Analysis
  • Cost-Benefit
  • Financial Analysis
ML / AI5
  • Predictive Analytics
  • XGBoost / RF / GBM
  • NLP / TF-IDF
  • Generative AI
  • Neural Networks
VIZ_LIBS4
  • Matplotlib
  • Seaborn
  • ggplot2
  • Data Storytelling
PROCESS4
  • Agile / Scrum
  • JIRA
  • Confluence
  • Stakeholder Comms
DOMAIN4
  • Healthcare / Pharma
  • Travel · Mobility
  • Labor / Workforce
  • Sustainability
0X.05 // FIELD_BRIEFING_2026 CLASSIFIED · ANALYST POV

The role is changing.
I’m built for what comes next.

● BRIEFING
SOURCE: PUBLIC INTEL
DATED: 2026 Q2
CLEARANCE: OPEN
SIGNAL_01 // AGENTIC_ANALYTICS

AI agents now offload 30–40% of routine BA work

Microsoft Copilot, Power BI Copilot, and emerging agentic systems are absorbing the grunt of requirements drafting, data prep, and first-pass analysis. The valuable work shifts upstream: framing the question and downstream: judging the answer.

30–40% routine tasks automated
// MEHTA STANCE I co-led GenAI rollout at Alexion and design dashboards Copilot can extend, not replace. I treat agents as reach amplifiers, not threat vectors.
SIGNAL_02 // SELF_SERVICE_ASCENT

By 2026, 90% of analytics consumers can generate their own content

Natural language querying (Copilot, ThoughtSpot) collapses the “ticket-an-analyst” pattern. The analyst’s value moves to governance, semantic modeling, and trust — making the self-serve layer correct by construction.

90% consumers self-generating
// MEHTA STANCE My 80% validation-effort win at Alexion wasn’t just a dashboard — it was a self-service substrate. That mindset is what 2026 BI demands.
SIGNAL_03 // FABRIC_CONVERGENCE

Microsoft Fabric is now the default enterprise BI stack

Fabric + OneLake + Power BI Copilot has consolidated what used to be three or four tools into one governed surface. Snowflake remains a key warehouse, but Fabric reshapes how Power BI analysts ship.

$420B market trajectory by 2027
// MEHTA STANCE Power BI + Snowflake + DAX is my native habitat. Migrating that fluency into Fabric is a reading, not a rewrite.
SIGNAL_04 // STORYTELLING_PREMIUM

Communication now ranks equal to technical skill in BA postings

Presentation skills appear in 14%+ of analyst postings. As tooling democratizes raw analysis, the differentiator becomes turning evidence into a decision a VP will sign. The narrative wins.

1:1 tech : comms weight
// MEHTA STANCE I co-presented at a 200-person GenAI event and translate analytics for both Finance and IT stakeholders. Storytelling is in the muscle, not the resume.
SIGNAL_05 // PREDICTIVE_DEFAULT

Forecasting is the new minimum, not a flex

“What happened” dashboards no longer cut it. Modern BAs are expected to ship scenario analysis, demand forecasts, and risk simulations as a baseline — with predictive AI threaded into the BI layer itself.

+40% Mehta forecast accuracy
// MEHTA STANCE Holiday Horizons shipped a 40% lift in travel demand forecasting. I treat predictive as part of the BI deliverable, not a separate workstream.
SIGNAL_06 // GOVERNANCE_RISES

AI governance is the fastest-growing BA adjacency

As GenAI and agentic systems enter analytics workflows, employers want analysts who can frame data lineage, model risk, and decision auditability. This is where former “just-the-dashboard” roles graduate into trusted advisory work.

3 / 3 Alexion pain points framed
// MEHTA STANCE At Alexion I used abstraction-ladder analysis to surface 3 high-impact operational pain points — a governance-grade habit, applied early.
0X.06 // CREDENTIALS VERIFIED
NORTHEASTERN UNIVERSITY · BOSTON, MAGPA 3.63

Master of Science · Data Analytics Engineering

Conferred May 2025
COURSEWORK // Foundations of Data Analytics Engineering · Data Management for Analytics · Computation & Visualization · Neural Networks · Natural Language Processing · Data Mining · Economic Decision Making
UNIVERSITY OF MUMBAI · SAKECB.E.

Bachelor of Engineering · Computer Science

Conferred May 2023
COURSEWORK // Database Management Systems · Data Warehousing & Mining · Big Data Analytics · Machine Learning · Social Media Analytics · Algorithm Analysis
0X.07 // QUERY_CONSOLE TYPE /HELP
mehta@decoder ~ % v2026.04 — INTERACTIVE
// Welcome to DECODER. Recruiters: try /hire — others: /help
mehta@decoder ~ % whoami
aakash_j_mehta · BI operative · M.S. Data Analytics Engineering · Boston, MA
mehta@decoder ~ % cat readme.md
Available for full-time Business / Data / BI Analyst roles.
OPT / STEM-OPT verified · seeking E-Verify employers for STEM extension.
 
> ↵ ENTER
0X.08 // DEPLOYMENT_PROTOCOL CHANNEL_OPEN

Deploy this operative.

Open to full-time Business Analyst, Data Analyst, and BI roles across Boston, NYC, Chicago, Dallas, LA, Miami, Phoenix, and Tampa. Bring me a messy dataset, a confused stakeholder, and a deadline — I’ll bring back a decision.

● STATUS: AVAILABLE  ·  OPT/STEM_OPT VERIFIED  ·  E-VERIFY EMPLOYERS PREFERRED

EMAIL aakashmehta893@gmail.com → PHONE (857) 706-9709 → LINKEDIN /in/aakashmehta1801 → LEGACY_SITE mehtaaakash.super.site → QUICK_COPY copy email →
BUSINESS INTELLIGENCE▮ DATA STORYTELLING▮ POWER BI · DAX · SNOWFLAKE▮ FORECAST ACCURACY +40%▮ CLOUD COST REDUCTION −15%▮ VALIDATION EFFORT −80%▮ GENAI · COPILOT · AGENTIC ANALYTICS▮ NORTHEASTERN UNIVERSITY · M.S.▮ BOSTON · NYC · CHI · DAL · LA · MIA · TPA · PHX▮ OPT / STEM-OPT VERIFIED▮ BUSINESS INTELLIGENCE▮ DATA STORYTELLING▮ POWER BI · DAX · SNOWFLAKE▮ FORECAST ACCURACY +40%▮ CLOUD COST REDUCTION −15%▮ VALIDATION EFFORT −80%▮ GENAI · COPILOT · AGENTIC ANALYTICS▮ NORTHEASTERN UNIVERSITY · M.S.▮ BOSTON · NYC · CHI · DAL · LA · MIA · TPA · PHX▮ OPT / STEM-OPT VERIFIED▮