10 years in Marketing & Sales. For the last 5 years have been working in Google & Snap on mobile apps & gaming businesses growth,

leading ATL, BTL, performance and influencer marketing campaigns.

Conducted research to understand the root causes of the problem and hypothesized that providing daily insights and practices, along with a visual roadmap of their progress, would help users stay motivated and engaged with the app. We then implemented this approach and tested its effectiveness, which resulted in a significant increase in retention and engagement rates. Based on these positive results, we continued to develop and personalize this feature to provide even more value to our users.

Socials growth

• Telegram chat: 100 -> 4500 subscribers Discord: 150 -> 1700 server participants

• Discord ER: 0 -> 4.36%

• Twitter: 0 -> 115 followers

• Reddit: 0 -> 3000 community karma

Achievements

• Set up the whole content structure with announcements, weekly events, streams and raffles

• Created trailer of the game and promoted it on Reddit with organic reach

• Developed Social Media Pages Design w/ banners, profile banners and icons.

• Hosted 3 AmAs and 1 NFT raffle which brought around ~300 active players to the beta version of the game.

• Set up google analytics to track link clicks and engagement

Challenge: Optimization of Retail Space: We have a certain number of shelves in a store and various display zones that must be represented. The task is to fill the shelves in such a way that the chosen layout is maximally effective in terms of revenue and also meets business requirements.

Solution: I wrote a library in Python that, based on sales data and store size, calculates how the retail space should be filled. It utilizes a Beam Search algorithm that, at each step, retains not just one best solution, but the top N solutions. This approach allows for diversity (as the best solution at each step does not always yield the best sequence) and maintains a reasonable breadth of search by not analyzing very poor filling options. This solution is automated, simplifying its use for business representatives.

Outcome: This solution will be used for zoning in the deployment of new stores and the redesign of old ones

As a founder:

• Increasing team from 2 people to 12+

• Entering regional retail networks and airports' Duty Free

• Launching sales on online marketplaces

• Raising investment from business angel

Launched 2 startups: candies with alcohol and another in creator economy

Now, as a venture partner at Republic, I help investors identify opportunities, and know what they want from startups

Tackled the learning issue by implementing various personalized learning styles and improved the product checkout process by decreasing the clicks required for payment from 4 to 2 through A/B testing. This streamlined the checkout process, making it more efficient and user-friendly.

I've been leveraging LinkedIn to find remote positions.

How to write a selling CV/ cover letter, how to pass English-speaking interviews and negotiate offers.

I have found a remote position in 3 months with flexible working hours/unlimited vacation policy. I have survived 2 lay-offs waves but that can be just lucky

The business struggled to receive insights from customer reviews to improve product quality because they lacked the necessary details. I released a feature that allowed customers to select tags by category when evaluating a product (For example: Taste -> Sugary, Sour, Oversalted). This provided businesses with systematic customers feedback, which they used to make targeted improvements that resulted in the average goods rating increase by 20%.

As an iOS developer in FG BCS, a leading investment company in the Russian market, I contributed to their app for private investors.

I implemented a flow of transfer money from a user's account or cart to a card of another bank: users selected an account or a cart to transfer money from, next step they entered card PAN or a phone number and selected another user’s bank from the suggested list.

As CTO at PrimerAI, I developed an intelligent platform for personalized cosmetics suggestions using ML and AI, including OpenCV, GPT-4, and K-means clustering for skin tone detection and categorization. I employed a holistic approach in developing and implementing this web app, which analyzed users' skin tones using computer vision and unsupervised ML algorithms. My contributions covered all aspects of the project, including designing and building the frontend and backend of the web app, as well as administering Linux servers. This ensured a seamless, end-to-end product experience that catered to our users' needs.