Innovatria is an investment management firm focused on innovative technology companies that are publicly traded and have a confluence of technical indicators that suggest the best place to enter or exit positions. Financial instruments are typically options, stocks, and ETFs used for “Swing trading” or long-term holds.Methodologies include: CAN SLIM - a growth stock methodology created by William O'Neil which is a bullish trend following strategy for fast markets, with the goal of getting into the high growth stocks before the institutional funds are fully invested.Momentum trading - a methodology that looks at technical indicators, options order flow, futures, and macroeconomic factors to place well-timed bets on short-term stock movements.Options income trading - a methodology that looks at the mispricing of options premiums that result when there is more uncertainty created by outsized market moves.

OSIsoft makes the “PI System,” the market leader in the product category of data historians. The product category was under attack eroding its boundaries, to grow, the company needed to find a market segment that the “PI System” could be adapted to fit a new market’s a customer’s “jobs to be done.” • Led the team through a market requirements prioritization process based on Geoffrey Moore’s framework for “Crossing the Chasm” into mainstream adoption.• Of the 6 new markets, nominated 2 (data centers & “connected services”) as to their worthiness for market development.• Created “Go to Market” plans for these Developer/Partner Lead markets.• Created market opportunity sizing (TAM, SAM, Target), growth drivers & trends.• Utilizing Tableau and OSIsoft’s customer data warehouse, performed a customer cohort’s analysis to classify a customer’s software adoption pattern, and design a marketing campaign to re-activate dormant accounts.• Built relationships with internal leadership to understand their priorities and their hypothesis, which needed to be tested with data.• Well trained in IBM’s market intelligence engagement process – an end to end process for gathering stakeholder requirements, hypothesis testing, creating and delivering executive summaries and dashboards.Keywords: Data pipelines, Kafka, Hadoop, data wrangling, Trifacta, Python, R, Tableau, PowerBI, Storytelling, Excel, Microsoft Office, SQL, Enterprise Software, IoT, product marketing, product management, consumer insights, data science, business intelligence, database, marketing strategy, market research ,product roadmap, eCommerce, data lake, data historians, SCADA, Data Centers, RUP, Scrum, IT architecture.

Pure Systems was IBM’s new entry into the “converged infrastructure” product category comprised of pre-integrated compute, storage and networking modules. • Led qualitative and quantitative market research to understand customer & prospect needs by segment, barriers to adoption, competitive offerings, and sales channels.• Co-authored qualitative discussion guides and quantitative survey questions.• Collaborated with Industry Analysts (Gartner/IDC) on segment definitions, competitive wins, and mapping category forecasts to realized share.• Created IBM’s share of market dashboard based on 3rd party reporting and internal sales• Created sales battle cards.• Regularly presented to executives on product category share of market and competitive wins.• Worked as part of a virtual team across a global matrixed organization.During this period, IBM exceeded the competitive benchmark set by Cisco, when they launched their converged infrastructure family of products the prior year.

The System X brand was a $1.7B business providing IT hardware and systems management software based on the Intel x86 architecture.• Managed qualitative and quantitative market research programs including sell-through programs at computer retailers.• Collaborated with IBM’s product marketing managers on use cases, business partners and go to market plans.• Performed customer cohort analysis across all channels.• Quarterly presentations on market growth and IBM share with commentary on “big wins” that occasionally skewed results.• Collaborated on the creation of predictive analytic models.• Identified an emerging segment eventually called “density optimized” but it foretold the rise of the “Mega Data centers” that eventually became “Cloud Computing” and they significantly altered the buying behaviors of traditional IBM customers.• Worked as part of a virtual team across a global matrixed organization.During this period, the System X brand grew 24% from $1.7B to $2.1B

Demand Programs was the organization that ran all of IBM’s digital marketing campaigns, and the Data Strategist was the person that consulted with the IBM brands on their demand generation needs.•Subject matter expert (Master Data Management / Data Governance) of all internal and external data sources that fed the global marketing data warehouse.•Worked with multiple IBM brands eliciting their needs, budget and expected ROI’s•Collaborated with campaign managers in the creation of their marketing programs.•Created campaign audiences based on the results of Propensity to Buy and Market Basket models. •Created dashboards and executive presentations that showed the results•Collaborated on the development of Propensity to Buy models, Market Basket models, Customer Lifetime Value and used these work products for specific campaigns.•Expert in data wrangling, SQL query, data visualization reducing complexity to a story based on the data.

Nissan was the 6th largest auto manufacturer, and it had outsourced it IT and applications support to IBM. My role supported their marketing operations, dealers, service contracts and warranty operations. A few representative projects were:•Created an enterprise data architecture for customer data which became the corporate standard for how the company would treat customer data.•Enriched customer data residing in the Epiphany marketing automation system with household data provided by 3rd parties.•Gathered requirements and created reports for the Service Contract / Warranty claims data warehouse.